
Learning Bayesian Statistics
204 episodes — Page 3 of 5

Why Even Care About Science & Rationality
trailerProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meListen to the full episode: https://learnbayesstats.com/episode/97-probably-overthinking-statistical-paradoxes-allen-downey/Watch the interview: https://www.youtube.com/watch?v=KgesIe3hTe0Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie and Cory Kiser.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

How To Get Into Causal Inference
trailerProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meListen to the full episode: https://learnbayesstats.com/episode/97-probably-overthinking-statistical-paradoxes-allen-downey/Watch the interview: https://www.youtube.com/watch?v=KgesIe3hTe0Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie and Cory Kiser.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

S1 Ep 97#97 Probably Overthinking Statistical Paradoxes, with Allen Downey
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIn this episode, I had the pleasure of speaking with Allen Downey, a professor emeritus at Olin College and a curriculum designer at Brilliant.org. Allen is a renowned author in the fields of programming and data science, with books such as "Think Python" and "Think Bayes" to his credit. He also authors the blog "Probably Overthinking It" and has a new book by the same name, which he just released in December 2023.In this conversation, we tried to help you differentiate between right and wrong ways of looking at statistical data, discussed the Overton paradox and the role of Bayesian thinking in it, and detailed a mysterious Bayesian killer app!But that’s not all: we even addressed the claim that Bayesian and frequentist methods often yield the same results — and why it’s a false claim. If that doesn’t get you to listen, I don’t know what will!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie and Cory Kiser.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:LBS #41, Thinking Bayes, with Allen Downey: https://learnbayesstats.com/episode/41-think-bayes-allen-downey/Allen’s blog:

How to Choose & Use Priors, with Daniel Lee
trailerProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meListen to the full episode: https://learnbayesstats.com/episode/96-pharma-models-sports-analytics-stan-news-daniel-lee/Watch the interview: https://www.youtube.com/watch?v=lnq5ZPlup0EVisit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas and Luke Gorrie.

Becoming a Good Bayesian & Choosing Mentors, with Daniel Lee
trailerProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meListen to the full episode: https://learnbayesstats.com/episode/96-pharma-models-sports-analytics-stan-news-daniel-lee/Watch the interview: https://www.youtube.com/watch?v=lnq5ZPlup0EVisit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas and Luke Gorrie.

S1 Ep 96#96 Pharma Models, Sports Analytics & Stan News, with Daniel Lee
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meGetting Daniel Lee on the show is a real treat — with 20 years of experience in numeric computation; 10 years creating and working with Stan; 5 years working on pharma-related models, you can ask him virtually anything. And that I did…From joint models for estimating oncology treatment efficacy to PK/PD models; from data fusion for U.S. Navy applications to baseball and football analytics, as well as common misconceptions or challenges in the Bayesian world — our conversation spans a wide range of topics that I’m sure you’ll appreciate!Daniel studied Mathematics at MIT and Statistics at Cambridge University, and, when he’s not in front of his computer, is a savvy basketball player and… a hip hop DJ — you actually have his SoundCloud profile in the show notes if you’re curious!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas and Luke Gorrie.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Daniel on Linkedin: https://www.linkedin.com/in/syclik/Daniel on Twitter: https://twitter.com/djsyclikDaniel on GitHub: https://github.com/syclikDaniel's DJ profile:

S1 Ep 95#95 Unraveling Cosmic Mysteries, with Valerie Domcke
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meWelcome to another installment of our LBS physics deep dive! After exploring the world of experimental physics at CERN in our first video documentary in episode 93, we’ll stay in Geneva for this one, but this time we’ll dive into theoretical physics.We’ll explore mysterious components of the universe, like dark matter and dark energy. We’ll also see how the study of gravity intersects with the study of particle physics, especially when considering black holes and the early universe. Even crazier, we’ll see that there are actual experiments and observational projects going on to answer these fundamental questions!Our guide for this episode is Valerie Domcke, permanent research staff member at CERN, who did her PhD in Hamburg, Germany, and postdocs in Trieste and Paris.When she’s not trying to decipher the mysteries of the universe, Valerie can be found on boats, as she’s a big sailing fan.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls and Maksim Kuznecov.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Valerie’s webpage: https://theory.cern/roster/domcke-valerieValerie on Google Scholar:

S1 Ep 94#94 Psychometrics Models & Choosing Priors, with Jonathan Templin
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIn this episode, Jonathan Templin, Professor of Psychological and Quantitative Foundations at the University of Iowa, shares insights into his journey in the world of psychometrics.Jonathan’s research focuses on diagnostic classification models — psychometric models that seek to provide multiple reliable scores from educational and psychological assessments. He also studies Bayesian statistics, as applied in psychometrics, broadly. So, naturally, we discuss the significance of psychometrics in psychological sciences, and how Bayesian methods are helpful in this field.We also talk about challenges in choosing appropriate prior distributions, best practices for model comparison, and how you can use the Multivariate Normal distribution to infer the correlations between the predictors of your linear regressions.This is a deep-reaching conversation that concludes with the future of Bayesian statistics in psychological, educational, and social sciences — hope you’ll enjoy it!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca and Dante Gates.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Jonathan’s website: https://jonathantemplin.com/Jonathan on Twitter: https://twitter.com/DrJTemplinJonathan on Linkedin: https://www.linkedin.com/in/jonathan-templin-0239b07/Jonathan on...

S1 Ep 93#93 A CERN Odyssey, with Kevin Greif
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meThis is a very special episode. It is the first-ever LBS video episode, and it takes place in the heart of particle physics research -- the CERN 🍾I went onsite in Geneva, to visit Kevin Greif, a doctoral candidate in particle physics at UC Irvine, and we walked around the CERN campus, talking about particle physics, dark matter, dark energy, machine learning -- and a lot more!I still released the audio form of this episode, but I really thought and made it as a video-first episode, so I strongly recommend watching this one, as you’ll get a cool tour of the CERN campus and some of its experiments ;) I put the YouTube link in the show notes.I hope you'll enjoy this deep dive into all things physics. If you have any recommendations for other cool scientific places I should do a documentary about, please get in touch on Twitter @LearnBayesStats, or by email.This was literally a one-person endeavor — you may have noticed that I edited the video myself. So, if you liked it, please send this episode to your friends and colleagues -- and tell them to support the show on Patreon 😉 With enough support, that means I'll be able to continue with such in-depth content, and maybe, maybe, even pay for a professional video editor next time 🙈 Enjoy, my dear Bayesians, and best Bayesian wishes 🖖Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau and Luis Fonseca.Visit

S1 Ep 92#92 How to Make Decision Under Uncertainty, with Gerd Gigerenzer
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meI love Bayesian modeling. Not only because it allows me to model interesting phenomena and learn about the world I live in. But because it’s part of a broader epistemological framework that confronts me with deep questions — how do you make decisions under uncertainty? How do you communicate risk and uncertainty? What does being rational even mean?Thankfully, Gerd Gigerenzer is there to help us navigate these fascinating topics. Gerd is the Director of the Harding Center for Risk Literacy of the University of Potsdam, Germany.Also Director emeritus at the Max Planck Institute for Human Development, he is a former Professor of Psychology at the University of Chicago and Distinguished Visiting Professor at the School of Law of the University of Virginia. Gerd has written numerous awarded articles and books, including Risk Savvy, Simple Heuristics That Make Us Smart, Rationality for Mortals, and How to Stay Smart in a Smart World.As you’ll hear, Gerd has trained U.S. federal judges, German physicians, and top managers to make better decisions under uncertainty.But Gerd is also a banjo player, has won a medal in Judo, and loves scuba diving, skiing, and, above all, reading.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau and Luis Fonseca.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag...

S1 Ep 91#91, Exploring European Football Analytics, with Max Göbel
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meAs you may know, I’m kind of a nerd. And I also love football — I've been a PSG fan since I’m 5 years old, so I’ve lived it all with this club.. And yet, I’ve never done a European-centered football analytics episode because, well, the US are much more advanced when it comes to sports analytics.But today, I’m happy to say this day has come: a sports analytics episode where we can actually talk about European football. And that is thanks to Maximilan Göbel.Max is a post-doctoral researcher in Economics and Finance at Bocconi University in Milan. Before that, he did his PhD in Economics at the Lisbon School of Economics and Management. Max is a very passionate football fan and played himself for almost 25 years in his local football club. Unfortunately, he had to give it up when starting his PhD — don’t worry, he still goes to the gym, or goes running and sometimes cycling.Max is also a great cook, inspired by all kinds of Italian food, and an avid podcast listener — from financial news, to health and fitness content, and even a mysterious and entertaining Bayesian podcast…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau and Luis Fonseca.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Max’s website:

S1 Ep 90#90, Demystifying MCMC & Variational Inference, with Charles Margossian
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meWhat’s the difference between MCMC and Variational Inference (VI)? Why is MCMC called an approximate method? When should we use VI instead of MCMC?These are some of the captivating (and practical) questions we’ll tackle in this episode. I had the chance to interview Charles Margossian, a research fellow in computational mathematics at the Flatiron Institute, and a core developer of the Stan software.Charles was born and raised in Paris, and then moved to the US to pursue a bachelor’s degree in physics at Yale university. After graduating, he worked for two years in biotech, and went on to do a PhD in statistics at Columbia University with someone named… Andrew Gelman — you may have heard of him.Charles is also specialized in pharmacometrics and epidemiology, so we also talked about some practical applications of Bayesian methods and algorithms in these fascinating fields.Oh, and Charles’ life doesn’t only revolve around computers: he practices ballroom dancing and pickup soccer, and used to do improvised musical comedy!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar and Matt Rosinski.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Charles’ website: https://charlesm93.github.io/Charles on Twitter: https://twitter.com/charlesm993Charles on GitHub:

S1 Ep 89#89 Unlocking the Science of Exercise, Nutrition & Weight Management, with Eric Trexler
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIf you’ve ever tried to lose fat or gain muscle, you may have noticed… it’s not easy. But it’s precisely its complexity that makes the science of exercise and nutrition fascinating.This is the longest LBS episode so far, and you’ll understand why pretty quickly: we covered a very wide range of topics, starting with the concept of metabolic adaptation and how our physiology and brain react to caloric deficits or caloric surpluses.We also talked about the connection between metabolic adaptation and exercise energy compensation, shedding light on the interactions between the two, and how they make weight management more complex.Statistics are of utmost importance in these endeavors, so of course we touched on how Bayesian stats can help mitigate the challenges of low sample sizes and over-focus on average treatment effect.My guest for this marathon episode, is no other than Eric Trexler. Currently at the Department of Evolutionary Anthropology of Duke University, Eric conducts research on metabolism and cardiometabolic health. He has a PhD in Human Movement Science from UNC Chapel Hill, and has published dozens of peer-reviewed research papers related to exercise, nutrition, and metabolism.In addition, Eric is a former professional bodybuilder and has been coaching clients with goals related to health, fitness, and athletics since 2009.In other words, get comfy for a broad and nerdy conversation about the mysteries related to energy expenditure regulation, weight management, and evolutionary mechanisms underpinning current health challenges.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio

S1 Ep 88#88 Bridging Computation & Inference in Artificial Intelligent Systems, with Philipp Hennig
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meToday, we’re gonna learn about probabilistic numerics — what they are, what they are good for, and how they relate computation and inference in artificial intelligent systems.To do this, I have the honor of hosting Philipp Hennig, a distinguished expert in this field, and the Chair for the Methods of Machine Learning at the University of Tübingen, Germany. Philipp studied in Heidelberg, also in Germany, and at Imperial College, London. Philipp received his PhD from the University of Cambridge, UK, under the supervision of David MacKay, before moving to Tübingen in 2011. Since his PhD, he has been interested in the connection between computation and inference. With international colleagues, he helped establish the idea of probabilistic numerics, which describes computation as Bayesian inference. His book, Probabilistic Numerics — Computation as Machine Learning, co-authored with Mike Osborne and Hans Kersting, was published by Cambridge University Press in 2022 and is also openly available online. So get comfy to explore the principles that underpin these algorithms, how they differ from traditional numerical methods, and how to incorporate uncertainty into the decision-making process of these algorithms.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar and Matt Rosinski.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Philipp on Twitter:...

S1 Ep 87#87 Unlocking the Power of Bayesian Causal Inference, with Ben Vincent
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meI’ll be honest — this episode is long overdue. Not only because Ben Vincent is a friend, fellow PyMC Labs developer, and outstanding Bayesian modeler. But because he works on so many fascinating topics — so I’m all the happier to finally have him on the show!In this episode, we’re gonna focus on causal inference, how it naturally extends Bayesian modeling, and how you can use the CausalPy open-source package to supercharge your Bayesian causal inference. We’ll also touch on marketing models and the pymc-marketing package, because, well, Ben does a lot of stuff ;)Ben got his PhD in neuroscience at Sussex University, in the UK. After a postdoc at the University of Bristol, working on robots and active vision, as well as 15 years as a lecturer at the Scottish University of Dundee, he switched to the private sector, working with us full time at PyMC Labs — and that is a treat!When he’s not working, Ben loves running 5k’s, cycling in the forest, lifting weights, and… learning about modern monetary theory.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Ben’s website: https://drbenvincent.github.io/Ben on GitHub: https://github.com/drbenvincentBen on Twitter:

S1 Ep 86#86 Exploring Research Synchronous Languages & Hybrid Systems, with Guillaume Baudart
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meThis episode is unlike anything I’ve covered so far on the show. Let me ask you: Do you know what a research synchronous language is? What about hybrid systems? Last try: have you heard of Zelus, or ProbZelus?If you answered “no” to one of the above, then you’re just like me! And that’s why I invited Guillaume Baudart for this episode — to teach us about all these fascinating topics!A researcher in the PARKAS team of Inria, Guillaume's research focuses on probabilistic and reactive programming languages. In particular, he works on ProbZelus, a probabilistic extension to Zelus, itself a research synchronous language to implement hybrid systems.To simplify, Zelus is a modeling framework to simulate the dynamics of systems both smooth and subject to discrete dynamics — if you’ve ever worked with ODEs, you may be familiar with these terms.If you’re not — great, Guillaume will explain everything in the episode! And I know it might sound niche, but this kind of approach actually has very important applications — such as proving that there are no bugs in a program.Guillaume did his PhD at École Normale Supérieure, in Paris, working on reactive programming languages and quasi-periodic systems. He then worked in the AI programming team of IBM Research, before coming back to the École Normale Supérieure, working mostly on reactive and probabilistic programming.In his free time, Guillaume loves spending time with his family, playing the violin with friends, and… cooking!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt

S1 Ep 85#85 A Brief History of Sports Analytics, with Jim Albert
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIn this episode, I am honored to talk with a legend of sports analytics in general, and baseball analytics in particular. I am of course talking about Jim Albert.Jim grew up in the Philadelphia area and studied statistics at Purdue University. He then spent his entire 41-year academic career at Bowling Green State University, which gave him a wide diversity of classes to teach – from intro statistics through doctoral level.As you’ll hear, he’s always had a passion for Bayesian education, Bayesian modeling and learning about statistics through sports. I find that passion fascinating about Jim, and I suspect that’s one of the main reasons for his prolific career — really, the list of his writings and teachings is impressive; just go take a look at the show notes.Now an Emeritus Professor of Bowling Green, Jim is retired, but still an active tennis player and writer on sports analytics — his blog, “Exploring Baseball with R”, is nearing 400 posts!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Jim’s website: https://bayesball.github.io/Jim’s baseball blog: https://baseballwithr.wordpress.com/Jim on...

S1 Ep 84#84 Causality in Neuroscience & Psychology, with Konrad Kording
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meThis is another installment in our neuroscience modeling series! This time, I talked with Konrad Kording, about the role of Bayesian stats in neuroscience and psychology, electrophysiological data to study what neurons do, and how this helps explain human behavior.Konrad studied at ETH Zurich, then went to UC London and MIT for his postdocs. After a decade at Northwestern University, he is now Penn Integrated Knowledge Professor at the University of Pennsylvania.As you’ll hear, Konrad is particularly interested in the question of how the brain solves the credit assignment problem and similarly how we should assign credit in the real world (through causality). Building on this, he is also interested in applications of causality in biomedical research.And… he’s also a big hiker, skier and salsa dancer!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Konrad’s lab: https://kordinglab.com/Konrad’s lab on GitHub: https://github.com/KordingLabKonrad’s lab on Twitter: https://twitter.com/KordingLabLBS #81, Neuroscience of Perception: Exploring the Brain, with Alan Stocker:

S1 Ep 83#83 Multilevel Regression, Post-Stratification & Electoral Dynamics, with Tarmo Jüristo
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meOne of the greatest features of this podcast, and my work in general, is that I keep getting surprised. Along the way, I keep learning, and I meet fascinating people, like Tarmo Jüristo.Tarmo is hard to describe. These days, he’s heading an NGO called Salk, in the Baltic state called Estonia. Among other things, they are studying and forecasting elections, which is how we met and ended up collaborating with PyMC Labs, our Bayesian consultancy.But Tarmo is much more than that. Born in 1971 in what was still the Soviet Union, he graduated in finance from Tartu University. He worked in finance and investment banking until the 2009 crisis, when he quit and started a doctorate in… cultural studies. He then went on to write for theater and TV, teaching literature, anthropology and philosophy. An avid world traveler, he also teaches kendo and Brazilian jiu-jitsu.As you’ll hear in the episode, after lots of adventures, he established Salk, and they just used a Bayesian hierarchical model with post-stratification to forecast the results of the 2023 Estonian parliamentary elections and target the campaign efforts to specific demographics.Oh, and let thing: Tarmo is a fan of the show — I told you he was a great guy ;)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh and Grant Pezzolesi.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Tarmo on GitHub: https://github.com/tarmojuristoTarmo on...

S1 Ep 82#82 Sequential Monte Carlo & Bayesian Computation Algorithms, with Nicolas Chopin
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with me------------------------------------------------------------------------------Max Kochurov’s State of Bayes Lecture Series: https://www.youtube.com/playlist?list=PL1iMFW7frOOsh5KOcfvKWM12bjh8zs9BQSign up here for upcoming lessons: https://www.meetup.com/pymc-labs-online-meetup/events/293101751/------------------------------------------------------------------------------We talk a lot about different MCMC methods on this podcast, because they are the workhorses of the Bayesian models. But other methods exist to infer the posterior distributions of your models — like Sequential Monte Carlo (SMC) for instance. You’ve never heard of SMC? Well perfect, because Nicolas Chopin is gonna tell you all about it in this episode!A lecturer at the French university of ENSAE since 2006, Nicolas is one of the world experts on SMC. Before that, he graduated from Ecole Polytechnique and… ENSAE, where he did his PhD from 1999 to 2003.Outside of work, Nicolas enjoys spending time with his family, practicing aikido, and reading a lot of books.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady and Kurt TeKolste.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Old episodes...

S1 Ep 81#81 Neuroscience of Perception: Exploring the Brain, with Alan Stocker
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meDid you know that the way your brain perceives speed depends on your priors? And it’s not the same at night? And it’s not the same for everybody?This is another of these episodes I love where we dive into neuroscience, how the brain works, and how it relates to Bayesian stats. It’s actually a follow-up to episode 77, where Pascal Wallisch told us how the famous black and blue dress tells a lot about our priors about how we perceive the world. So I strongly recommend listening to episode 77 first, and then come back here, to have your mind blown away again, this time by Alan Stocker.Alan was born and raised in Switzerland. After a PhD in physics at ETH Zurich, he somehow found himself doing neuroscience, during a postdoc at NYU. And then he never stopped — still leading the Computational Perception and Cognition Laboratory of the University of Pennsylvania.But Alan is also a man of music (playing the piano when he can), a man of coffee (he’ll never refuse an olympia cremina or a kafatek) and a man of the outdoors (he loves trashing through deep powder with his snowboard).Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady and Kurt TeKolste.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Alan’s website: https://www.sas.upenn.edu/~astocker/lab/members-files/alan.phpNoise characteristics and prior expectations in human visual speed perception: https://www.nature.com/articles/nn1669Combining efficient coding with

S1 Ep 80#80 Bayesian Additive Regression Trees (BARTs), with Sameer Deshpande
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m sure you know at least one Bart. Maybe you’ve even used one — but you’re not proud of it, because you didn’t know what you were doing. Thankfully, in this episode, we’ll go to the roots of regression trees — oh yeah, that’s what BART stands for. What were you thinking about?Our tree expert will be no one else than Sameer Deshpande. Sameer is an assistant professor of Statistics at the University of Wisconsin-Madison. Prior to that, he completed a postdoc at MIT and earned his Ph.D. in Statistics from UPenn.On the methodological front, he is interested in Bayesian hierarchical modeling, regression trees, model selection, and causal inference. Much of his applied work is motivated by an interest in understanding the long-term health consequences of playing American-style tackle football. He also enjoys modeling sports data and was a finalist in the 2019 NFL Big Data Bowl.Outside of Statistics, he enjoys cooking, making cocktails, and photography — sometimes doing all of those at the same time…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, and Arkady.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Sameer’s website: https://skdeshpande91.github.io/Sameer on GitHub: https://github.com/skdeshpande91Sameer on Twitter: https://twitter.com/skdeshpande91 Sameer on Google Scholar: https://scholar.google.com/citations?user=coVrnWIAAAAJ&hl=enLBS #50 Ta(l)king Risks & Embracing...

S1 Ep 79#79 Decision-Making & Cost Effectiveness Analysis for Health Economics, with Gianluca Baio
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Decision-making and cost effectiveness analyses rarely get as important as in the health systems — where matters of life and death are not a metaphor. Bayesian statistical modeling is extremely helpful in this field, with its ability to quantify uncertainty, include domain knowledge, and incorporate causal reasoning.Specialized in all these topics, Gianluca Baio was the person to talk to for this episode. He’ll tell us about this kind of models, and how to understand them.Gianluca is currently the head of the department of Statistical Science at University College London. He studied Statistics and Economics at the University of Florence (Italy), and completed a PhD in Applied Statistics, again at the beautiful University of Florence.He’s also a very skilled pizzaiolo — so now I have two reasons to come back to visit Tuscany…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, and Arkady.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Gianluca’s website: https://gianluca.statistica.it/Gianluca on GitHub: https://github.com/giabaio Gianluca on Mastodon: https://mas.to/@gianlubaioGianluca on Twitter: https://twitter.com/gianlubaioGianluca on Linkedin: https://www.linkedin.com/in/gianluca-baio-b893879/Gianluca’s articles on arXiv:

S1 Ep 78#78 Exploring MCMC Sampler Algorithms, with Matt D. Hoffman
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Matt Hoffman has already worked on many topics in his life – music information retrieval, speech enhancement, user behavior modeling, social network analysis, astronomy, you name it.Obviously, picking questions for him was hard, so we ended up talking more or less freely — which is one of my favorite types of episodes, to be honest.You’ll hear about the circumstances Matt would advise picking up Bayesian stats, generalized HMC, blocked samplers, why do the samplers he works on have food-based names, etc.In case you don’t know him, Matt is a research scientist at Google. Before that, he did a postdoc in the Columbia Stats department, working with Andrew Gelman, and a Ph.D at Princeton, working with David Blei and Perry Cook.Matt is probably best known for his work in approximate Bayesian inference algorithms, such as stochastic variational inference and the no-U-turn sampler, but he’s also worked on a wide range of applications, and contributed to software such as Stan and TensorFlow Probability.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode and Gabriel Stechschulte.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Matt’s website: http://matthewdhoffman.com/Matt on Google Scholar: https://scholar.google.com/citations?hl=en&user=IeHKeGYAAAAJ&view_op=list_worksThe No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo: https://www.jmlr.org/papers/volume15/hoffman14a/hoffman14a.pdfTuning-Free Generalized Hamiltonian Monte Carlo:

S1 Ep 77#77 How a Simple Dress Helped Uncover Hidden Prejudices, with Pascal Wallisch
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I love dresses. Not on me, of course — I’m not nearly elegant enough to pull it off. Nevertheless, to me, dresses are one of the most elegant pieces of clothing ever invented.And I like them even more when they change colors. Well, they don’t really change colors — it’s the way we perceive the colors that can change. You remember that dress that looked black and blue to some people, and white and gold to others? Well that’s exactly what we’ll dive into and explain in this episode.Why do we literally see the world differently? Why does that even happen beyond our consciousness, most of the time? And cherry on the cake: how on Earth could this be related to… priors?? Yes, as in Bayesian priors!Pascal Wallisch will shed light on all these topics in this episode. Pascal is a professor of Psychology and Data Science at New York University, where he studies a diverse range of topics including perception, cognitive diversity, the roots of disagreement and psychopathy.Originally from Germany, Pascal did his undergraduate studies at the Free University of Berlin. He then received his PhD from the University of Chicago, where he studied visual perception.In addition to scientific articles on psychology and neuroscience, he wrote multiple books on scientific computing and data science. As you’ll hear, Pascal is a wonderful science communicator, so it's only normal that he also writes for a general audience at Slate or the Creativity Post, and has given public talks at TedX and Think and Drink.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R and Nicolas Rode.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Pascal’s website: https://blog.pascallisch.net/about/Pascal on Twitter:

S1 Ep 76#76 The Past, Present & Future of Stan, with Bob Carpenter
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!How does it feel to switch careers and start a postdoc at age 47? How was it to be one of the people who created the probabilistic programming language Stan? What should the Bayesian community focus on in the coming years?These are just a few of the questions I had for my illustrious guest in this episode — Bob Carpenter. Bob is, of course, a Stan developer, and comes from a math background, with an emphasis on logic and computer science theory. He then did his PhD in cognitive and computer sciences, at the University of Edinburgh.He moved from a professor position at Carnegie Mellon to industry research at Bell Labs, to working with Andrew Gelman and Matt Hoffman at Columbia University. Since 2020, he's been working at Flatiron Institute, a non-profit focused on algorithms and software for science.In his free time, Bob loves to cook, see live music, and play role playing games — think Monster of the Week, Blades in Dark, and Fate.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin and Raphaël R.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Bob’s website: https://bob-carpenter.github.ioBob on GitHub: https://github.com/bob-carpenterBob on Google Scholar: https://scholar.google.com.au/citations?user=kPtKWAwAAAAJ&hl=enStat modeling blog: https://statmodeling.stat.columbia.eduStan home page:

S1 Ep 75#75 The Physics of Top Gun 2 Maverick, with Jason Berndt
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!If you’re a nerd like me, you’re always curious about the physics of any situation. So, obviously, when I watched Top Gun 2, I became fascinated by the aerodynamics of fighters jets. And it so happens that one of my friends used to be a fighter pilot for the Canadian army… Immediately, I thought this would make for a cool episode — and here we are!Actually, Jason Berndt wanted to be a pilot from the age of 3. When he was 6, he went to an air show, and then specifically wanted to become a fighter pilot. In his teens, he learned how to fly saliplanes, small single engine aircrafts. At age 22, he got a bachelor’s in aero engineering from the royal military college, and then — well, he’ll tell you the rest in the episode.Now in his thirties, he owns real estate and created his own company, My Two Brows, selling temporary eyebrow tattoos — which, weirdly enough, is actually related to his time in the army…In his free time, Jason plays the guitar, travels around the world (that’s actually how we met), and loves chasing adrenaline however he can (paragliding, scuba diving, you name it!).Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin and Raphaël R.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:My Two Brows website: https://mytwobrows.com/My Two Brows on Instagram: https://www.instagram.com/my_two_brows/My Two Brows on YouTube: https://www.youtube.com/channel/UC6eQgQ4qoGE2RStDJkumUGgPyMC Labs Workshop – Hierarchical Bayesian Modeling of Survey Data with Post-stratification:

S1 Ep 74#74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!We need to talk. I had trouble writing this introduction. Not because I didn’t know what to say (that’s hardly ever an issue for me), but because a conversation with Adrian Seyboldt always takes deliciously unexpected turns.Adrian is one of the most brilliant, interesting and open-minded person I know. It turns out he’s courageous too: although he’s not a fan of public speaking, he accepted my invitation on this show — and I’m really glad he did!Adrian studied math and bioinformatics in Germany and now lives in the US, where he enjoys doing maths, baking bread and hiking.We talked about the why and how of his new project, Nutpie, a more efficient implementation of the NUTS sampler in Rust. We also dived deep into the new ZeroSumNormal distribution he created and that’s available from PyMC 4.2 onwards — what is it? Why would you use it? And when?Adrian will also tell us about his favorite type of models, as well as what he currently sees as the biggest hurdles in the Bayesian workflow.Each time I talk with Adrian, I learn a lot and am filled with enthusiasm — and now I hope you will too!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey and Andreas Kröpelin.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:LBS on Twitter: https://twitter.com/LearnBayesStatsLBS on Linkedin: https://www.linkedin.com/company/learn-bayes-stats/Adrian on GitHub: https://github.com/aseyboldtNutpie repository:

S1 Ep 73#73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica Hullman
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m guessing you already tried to communicate the results of a statistical model to non-stats people — it’s hard, right? I’ll be honest: sometimes, I even prefer to take notes during meetings than doing that… But shhh, that’s out secret.But all of this was before. Before I talked with Jessica Hullman. Jessica is the Ginny Rometty associate professor of computer science at Northwestern University.Her work revolves around how to design interfaces to help people draw inductive inferences from data. Her research has explored how to best align data-driven interfaces and representations of uncertainty with human reasoning capabilities, which is what we’ll mainly talk about in this episode.Jessica also tries to understand the role of interactive analysis across different stages of a statistical workflow, and how to evaluate data visualization interfaces.Her work has been awarded with multiple best paper and honorable mention awards, and she frequently speaks and blogs on topics related to visualization and reasoning about uncertainty — as usual, you’ll find the links in the show notes.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox and Trey Causey.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)General links from the show:Jessica’s website: http://users.eecs.northwestern.edu/~jhullman/ Jessica on Twitter: https://twitter.com/JessicaHullmanMidwest Uncertainty Collective: https://mucollective.northwestern.edu/Jessica’s posts on Andrew Gelman’s blog:

S1 Ep 72#72 Why the Universe is so Deliciously Crazy, with Daniel Whiteson
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!What happens inside a black hole? Can we travel back in time? Why is the Universe even here? This is the type of chill questions that we’re all asking ourselves from time to time — you know, when we’re sitting on the beach.This is also the kind of questions Daniel Whiteson loves to talk about in his podcast, “Daniel and Jorge Explain the Universe”, co-hosted with Jorge Cham, the author of PhD comics. Honestly, it’s one of my favorite shows ever, so I warmly recommend it. Actually, if you’ve ever hung out with me in person, there is a high chance I started nerding out about it…Daniel is, of course, a professor of physics, at the University of California, Irvine, and also a researcher at CERN, using the Large Hadron Collider to search for exotic new particles — yes, these are particles that put little umbrellas in their drinks and taste like coconut.On his free time, Daniel loves reading, sailing and baking — I can confirm that he makes a killer Nutella roll!Oh, I almost forgot: Daniel and Jorge wrote two books — We Have No Idea and FAQ about the Universe — which, again, I strongly recommend. They are among my all-time favorites.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek and Paul Cox.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:PyMC Labs Meetup, Dec 8th 2022, A Candle in the Dark – How to Use Hierarchical Post-Stratification with Noisy Data: https://www.meetup.com/pymc-labs-online-meetup/events/289949398/Daniel’s website: https://sites.uci.edu/daniel/Daniel on Twitter:

S1 Ep 71#71 Artificial Intelligence, Deepmind & Social Change, with Julien Cornebise
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!This episode will show you different sides of the tech world. The one where you research and apply algorithms, where you get super excited about image recognition and AI-generated art. And the one where you support social change actors — aka the “AI for Good” movement.My guest for this episode is, quite naturally, Julien Cornebise. Julien is an Honorary Associate Professor at UCL. He was an early researcher at DeepMind where he designed its early algorithms. He then worked as a Director of Research at ElementAI, where he built and led the London office and “AI for Good” unit.After his theoretical work on Bayesian methods, he had the privilege to work with the NHS to diagnose eye diseases; with Amnesty International to quantify abuse on Twitter and find destroyed villages in Darfur; with Forensic Architecture to identify teargas canisters used against civilians.Other than that, Julien is an avid reader, and loves dark humor and picking up his son from school at the 'hour of the daddies and the mommies”.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek and Paul Cox.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Julien’s website: https://cornebise.com/julien/Julien on Twitter: https://twitter.com/JCornebiseJulien on LinkedIn:

S1 Ep 70#70 Teaching Bayes for Biology & Biological Engineering, with Justin Bois
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Back in 2016, when I started dedicating my evenings and weekends to learning how to code and do serious stats, I was a bit lost… Where do I start? Which language do I pick? Why are all those languages just named with one single letter??Then I found some stats classes by Justin Bois — and it was a tremendous help to get out of that wood (and yes, this was a pun). I really loved Justin’s teaching because he was making the assumptions explicit, and also explained them — which was so much more satisfying to my nerdy brain, which always wonders why we’re making this assumption and not that one.So of course, I’m thrilled to be hosting Justin on the show today! Justin is a Teaching Professor in the Division of Biology and Biological Engineering at Caltech, California, where he also did his PhD. Before that, he was a postdoc in biochemistry at UCLA, as well as the Max Planck Institute in Dresden, Germany.Most importantly for the football fans, he’s a goalkeeper — actually, the day before recording, he saved two penalty kicks… and even scored a goal! A big fan of Los Angeles football club, Justin is a also a magic enthusiast — he is indeed a member of the Magic Castle…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken and Or Duek.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Justin’s website: http://bois.caltech.edu/index.html Justin on GitHub: https://github.com/justinbois/

S1 Ep 69#69 Why, When & How to use Bayes Factors, with Jorge Tendeiro
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!A great franchise comes with a great rivalry: Marvel has Iron Man and Captain America; physics has General Relativity and Quantum Physics; and Bayesian stats has Posterior Estimation and… Bayes Factors!A few months ago, I had the pleasure of hosting EJ Wagenmakers, to talk about these topics. This time, I’m talking with Jorge Tendeiro, who has a different perspective on Null Hypothesis Testing in the Bayesian framework, and its relationship with generative models and posterior estimation.But this is not your classic, click-baity podcast, and I’m not interested in pitching people against each other. Instead, you’ll hear Jorge talk about the other perspective fairly, before even giving his take on the topic. Jorge will also tell us about the difficulty of arguing through papers, and all the nuances you lose compared to casual discussions.But who is Jorge Tendeiro? He is a professor at Hiroshima University in Japan, and he was recommended to me by Pablo Bernabeu, a listener of this very podcast.Before moving to Japan, Jorge studied math and applied stats at the University of Porto, and did his PhD in the Netherlands. He focuses on item response theory (specifically person fit analysis), and, of course, Bayesian statistics, mostly Bayes factors.He’s also passionate about privacy issues in the 21st century, an avid Linux user since 2006, and is trying to get the hang of the Japanese language.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas and Robert Yolken.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Jorge’s website: https://www.jorgetendeiro.com/

Ep 68#68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Hosting someone like Kevin Murphy on your podcast is… complicated. Not because Kevin himself is complicated (he’s delightful, don’t make me say what I didn’t say!), but because all the questions I had for him amounted to a 12-hour show.Sooooo, brace yourselves folks!No, I'm kidding. Of course I didn’t do that folks, Kevin has a life! This life started in Ireland, where he was born. He grew up in England and got his BA from the University of Cambridge. After his PhD at UC Berkeley, he did a postdoc at MIT, and was an associate professor of computer science and statistics at the University of British Columbia in Vancouver, Canada, from 2004 to 2012. After getting tenure, he went to Google in California in 2011 on his sabbatical and then ended up staying. He currently runs a team of about 8 researchers inside of Google Brain working on generative models, optimization, and other, as Kevin puts it, “basic” research topics in AI/ML. He has published over 125 papers in refereed conferences and journals, as well 3 textbooks on machine learning published in 2012, 2022 and the last one coming in 2023. You may be familiar with his 2012 book, as it was awarded the DeGroot Prize for best book in the field of statistical science.Outside of work, Kevin enjoys traveling, outdoor sports (especially tennis, snowboarding and scuba diving), as well as reading, cooking, and spending time with his family.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha, Scott Anthony Robson, David Haas and Robert Yolken.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Kevin’s website:

S1 Ep 67#67 Exoplanets, Cool Worlds & Life in the Universe, with David Kipping
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Is there life in the Universe? It doesn’t get deeper than this, does it? And yet, why do we care about that? In the very small chance that there is other life in the Universe, we have even less chance to discover it, talk to it and meet it. So, why do we care?Well, it may surprise you but Bayesian statistics helps us think about these astronomical and — dare I say? — philosophical topics, as my guest, David Kipping, will brilliantly explain in this episode.David is an Associate Professor of Astronomy at Columbia University, where he leads the Cool Worlds Lab — I know, the name is awesome. His team’s research spans exoplanet discovery and characterization, the search for life in the Universe and developing novel approaches to our exploration of the cosmos.David also teaches astrostatistics, and his contributions to Bayesian statistics span astrobiology to exoplanet detection. He also hosts the Cool Worlds YouTube channel, with over half a million subscribers, that discusses his team’s work and broader topics within the field.Cool worlds, cool guest, cool episode.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha, Scott Anthony Robson, David Haas and Robert Yolken.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:David’s website: http://user.astro.columbia.edu/~dkipping/David on Twitter: https://twitter.com/david_kippingDavid’s YouTube channel:

S1 Ep 66#66 Uncertainty Visualization & Usable Stats, with Matthew Kay
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I have to confess something: I love challenges. And when you’re a podcaster, what’s a better challenge than dedicating an episode to… visualization? Impossible you say? Well, challenge accepted!Thankfully, I got the help of a visualization Avenger for this episode — namely, Matthew Kay. Matt is an Assistant Professor jointly appointed in Computer Science and Communications Studies at Northwestern University, where he co-directs the Midwest Uncertainty Collective — I know, it’s a pretty cool name for a lab.He works in human-computer interaction and information visualization, and especially in uncertainty visualization. He also builds tools to support uncertainty visualization in R. In particular, he’s the author of the tidybayes and ggdist R packages, and wrote the random variable interface in the posterior package.I promise, you won’t be uncertain about the importance of uncertainty visualization after that…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha and Scott Anthony Robson.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Matt on Twitter: https://twitter.com/mjskayMatt on GitHub: https://github.com/mjskay Matt’s website: https://www.mjskay.com/ Midwest Uncertainty Collective lab:

S1 Ep 65#65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo Vieira
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Folks, there are some new cool kids on the block. They are called PyMC, Aeppl, and Aesara, and it’s high time we give us a proper welcome!To do that, who better than one of the architects of the new PyMC 4.0 — Ricardo Vieira! In this episode, he’ll walk us through the inner workings of the newly released version of PyMC, telling us why the Aesara backend and the brand new RandomVariable operators constitute such strong foundations for your beloved PyMC models. He will also tell us about a self-contained PPL project called Aeppl, dedicated to converting model graphs to probability functions — pretty cool, right?Oh, in case you didn’t guess yet, Ricardo is a PyMC developer and data scientist at PyMC Labs. He spent several years teaching himself Statistics and Computer Science at the expense of his official degrees in Psychology and Neuroscience.So, get ready for efficient random generator functions, better probability evaluation functions, and a fully-fledged modern Bayesian workflow!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha and Scott Anthony Robson.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Ricardo on Twitter: https://twitter.com/RicardoV944Ricardo on GitHub: https://github.com/ricardoV94/Ricardo’s website: https://ricardov94.github.io/posts/PyMC, Aesara and Aeppl: The New Kids on The Block (YouTube...

S1 Ep 64#64 Modeling the Climate & Gravity Waves, with Laura Mansfield
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m sure you’ve already heard of gravitational waves, because my listeners are the coolest and smartest ever ;) But did you know about gravity waves? That’s right, waves in the sky due to gravity — sounds awesome, right?Well, I’m pretty sure that Laura Mansfield will confirm your prior. Currently a postdoc at Stanford University, Laura studies — guess what? — gravity waves and how they are represented in climate models. In particular, she uses Bayesian methods to estimate the uncertainty on the gravity wave components of the models.Holding a PhD from the University of Reading in the UK, her background is in atmospheric physics, but she’s interested in climate change and environmental issues.So seat back, chill out, and enjoy this physics-packed, aerial episode!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha and Scott Anthony Robson.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Laura on Twitter: https://twitter.com/lau_mansfieldLaura’s webpage: https://profiles.stanford.edu/laura-mansfieldJulia package for Gaussian Processes: https://github.com/STOR-i/GaussianProcesses.jl Julia implementation of the scikit-learn API:

S1 Ep 63#63 Media Mix Models & Bayes for Marketing, with Luciano Paz
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Inviting someone like Luciano Paz on a stats podcast is both a pleasure and a challenge — he does so many things brilliantly that you have too many questions to ask him…In this episode, I’ve chosen — not without difficulty — to focus on the applications of Bayesian stats in the marketing industry, especially Media Mix Models. Ok, I also asked Luciano about other topics — but you know me, I like to talk…Originally, Luciano studied physics. He then did a PhD and postdoc in neuroscience, before transitioning into industry. During his time in academia, he used stats, machine learning and data science concepts here and there, but not in a very organized way.But at the end of his postdoc, he got into PyMC — and that’s when everything changed… He loved the community and decided to hop on board to exit academia into a better life. After leaving academia, he worked at a company that wanted to do data science but that, for privacy reasons, didn’t have a lot of data. And now, Luciano is one of the folks working full time at the PyMC Labs consultancy.But Luciano is not only one of the cool nerds building this crazy Bayesian adventures. He also did a lot of piano and ninjutsu. Sooooo, don’t provoke him — either in the streets or at a karaoke bar…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh and Lin Yu Sha.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Luciano’s website: https://lucianopaz.github.io/Luciano on GitHub:

S1 Ep 62#62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!We talk a lot about generative modeling on this podcast — at least since episode 6, with Michael Betancourt! And an area where this way of modeling is particularly useful is healthcare, as Maria Skoularidou will tell us in this episode.Maria is a final year PhD student at the University of Cambridge. Her thesis is focused on probabilistic machine learning and, more precisely, towards using generative modeling in… you guessed it: healthcare!But her fields of interest are diverse: from theory and methodology of machine intelligence to Bayesian inference; from theoretical computer science to information theory — Maria is knowledgeable in a lot of topics! That’s why I also had to ask her about mixture models, a category of models that she uses frequently.Prior to her PhD, Maria studied Computer Science and Statistical Science at Athens University of Economics and Business. She’s also invested in several efforts to bring more diversity and accessibility in the data science world.When she’s not working on all this, you’ll find her playing the ney, trekking or rawing.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton and Jeannine Sue.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Maria on Twitter: https://twitter.com/skoularidouMaria on LinkedIn: https://www.linkedin.com/in/maria-skoularidou-1289b62a/Maria’s webpage:

S1 Ep 61#61 Why we still use non-Bayesian methods, with EJ Wagenmakers
The big problems with classic hypothesis testing are well-known. And yet, a huge majority of statistical analyses are still conducted this way. Why is it? Why are things so hard to change? Can you even do (and should you do) hypothesis testing in the Bayesian framework?I guess if you wanted to name this episode in a very Marvelian way, it would be “Bayes factors against the p-values of madness” — but we won’t do that, it wouldn’t be appropriate, would it?Anyways, in this episode, I’ll talk about all these very light and consensual topics with Eric-Jan Wagenmakers, a professor at the Psychological Methods Unit of the University of Amsterdam.For almost two decades, EJ has staunchly advocated the use of Bayesian inference in psychology. In order to lower the bar for the adoption of Bayesian methods, he is coordinating the development of JASP, an open-source software program that allows practitioners to conduct state-of-the-art Bayesian analyses with their mouse — the one from the computer, not the one from Disney.EJ has also written a children’s book on Bayesian inference with the title “Bayesian thinking for toddlers”. Rumor has it that he is also working on a multi-volume series for adults — but shhh, that’s a secret!EJ’s lab publishes regularly on a host of Bayesian topics, so check out his website, particularly when you are interested in Bayesian hypothesis testing. The same goes for his blog by the way, “BayesianSpectacles”.Wait, what’s that? EJ is telling me that he plays chess, squash, and that, most importantly, he enjoys watching arm wrestling videos on YouTube — yet another proof that, yes, you can find everything on YouTube.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:EJ’s website: http://ejwagenmakers.com/EJ on Twitter: https://twitter.com/EJWagenmakers“Bayesian Cognitive Modeling” book website:

S1 Ep 60#60 Modeling Dialogues & Languages, with J.P. de Ruiter
Why do we, humans, communicate? And how? And isn’t that a problem that to study communication we have to… communicate?Did you ever ask yourself that? Because J.P. de Ruiter did — and does everyday. But he’s got good reasons: JP is a cognitive scientist whose primary research focus is on the cognitive foundations of human communication. He aims to improve our understanding of how humans and artificial agents use language, gesture and other types of signals to effectively communicate with each other.Currently he has one of the two Bridge Professorship at Tufts University, and has been appointed in both the Computer Science and Psychology departments.In this episode, we’ll look at why Bayes is helpful in dialogue research, what the future of the field looks like to JP, and how he uses PyMC in his own teaching.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:JP’s page: https://sites.tufts.edu/hilab/people/Projecting the End of a Speaker's Turn – A Cognitive Cornerstone of Conversation: https://www.researchgate.net/publication/236787756_Projecting_the_End_of_a_Speaker's_Turn_A_Cognitive_Cornerstone_of_ConversationCognitive and social delays in the initiation of conversational repair: https://journals.uic.edu/ojs/index.php/dad/article/view/11388Using uh and um in spontaneous speaking: http://www.columbia.edu/~rmk7/HC/HC_Readings/Clark_Fox.pdfStatus of Frustrator as an Inhibitor of Horn-Honking Responses: https://www.tandfonline.com/doi/abs/10.1080/00224545.1968.9933615A Simplest Systematics for the Organization of Turn-Taking for Conversation:

S1 Ep 59#59 Bayesian Modeling in Civil Engineering, with Michael Faber
In large-scale one-off civil infrastructure, decision-making under uncertainty is part of the job, that’s just how it is. But, civil engineers don't get the luxury of building 10^6 versions of the bridge, offshore wind turbine or aeronautical structure to consider a relative frequency interpretation!And as you’ll hear, challenges don’t stop there: you also have to consider natural hazards such as earthquakes, rockfall and typhoons — in case you were wondering, civil engineering is not among the boring jobs!To talk about these original topics, I had the pleasure to host Michael Faber. Michael is a Professor at the Department of Built Environment at Aalborg University, Denmark, the President of the Joint Committee on Structural Safety and is a tremendously deep thinker on the Bayesian interpretation of probability as it pertains to the risk-informed management of big infrastructure.His research interests are directed on governance and management of risks, resilience and sustainability in the built environment — doing all that with Bayesian probabilistic modeling and applied Bayesian decision analysis, as you’ll hear.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Michael's profile on Aalborg University: https://vbn.aau.dk/en/persons/100493Michael's LinkedIn profile: https://www.linkedin.com/in/michael-havbro-faber-22898414/Statistics and Probability Theory - In Pursuit of Engineering Decision Support: https://link.springer.com/book/10.1007/978-94-007-4056-3Bayes in Civil Engineering - an abridged personal account of research and applications: https://www.linkedin.com/pulse/bayes-civil-engineering-michael-havbro-faberWebsite of the Joint Committee on Structural Safety (JCSS): https://www.jcss-lc.org/

S1 Ep 58#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao
You know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right?Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no to my soothing French accent, well, they didn’t say no…All of them were on the podcast already, so I’ll refer you to their solo episode for background on their background — aka backgroundception.Junpeng is a Data Scientist at Google, living in Zurich, Switzerland. Previously, he was a post-doc in Psychology and Cognitive Neuroscience. His current obsessions are time series and state space models. Osvaldo is a Researcher at CONICET in Argentina and the Department of Computer Science from Aalto University in Finland. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.Ravin is a data scientist at Google, living in Los Angeles. Previously he worked at Sweetgreen and SpaceX. He became interested in Bayesian statistics when trying to quantify uncertainty in operations. He is especially interested in decision science in business settings.You’ll make your own opinion, but I like their book because uses a hands-on approach, focusing on the practice of applied statistics. And you get to see how to use diverse libraries, like PyMC, Tensorflow Probability, ArviZ, Bambi, and so on. You’ll see what I’m talking about in this episode.To top it off, the book is fully available online at bayesiancomputationbook.com. If you want a physical copy (because you love those guys and wanna support them), go to CRC website and enter the code ASA18 at checkout for a 30% discount.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the...

S1 Ep 57#57 Forecasting French Elections, with… Mystery Guest
No, no, don't leave! You did not click on the wrong button. You are indeed on Alex Andorra’s podcast. The podcast that took the Bayesian world by a storm: “Learning Bayesian Statistics”, and that Barack Obama deemed “the best podcast in the whole galaxy” – or maybe Alex said that, I don’t remember.Alex made us discover new methods, new ideas, and mostly new people. But what do we really know about him? Does he even really exist? To find this out I put on my Frenchest beret, a baguette under my arm, and went undercover to try to find him.And I did ! So today for a special episode I, Rémi Louf, will be the one asking questions and making bad jokes with a French accent.Before letting him in, here’s what I got on him so far.By day, Alex is a Bayesian modeler at the PyMC Labs consultancy. By night, he doesn’t (yet) fight crime but he’s an open-source enthusiast and core contributor to PyMC and ArviZ.An always-learning statistician, Alex loves building models and studying elections and human behavior.When he’s not working, he loves hiking, exercising, meditating and reading nerdy books and novels. He also loves chocolate a bit too much, but he doesn’t like talking about it – he prefers eating it.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Alex on Twitter: https://twitter.com/alex_andorraAlex on GitHub: https://github.com/AlexAndorraAlex on LinkedIn: https://www.linkedin.com/in/aandorra-pollsposition/Intuitive Bayes Introductory Course:

S1 Ep 56#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa Ness
Did you know there is a relationship between the size of firetrucks and the amount of damage down to a flat during a fire? The bigger the truck sent to put out the fire, the bigger the damages tend to be. The solution is simple: just send smaller firetrucks!Wait, that doesn’t sound right, does it? Our brain is a huge causal machine, so it can instinctively feel it’s not credible that size of truck and amount of damage done are causally related: there must be another variable explaining the correlation. Here, it’s of course the seriousness of the fire — even better, it’s the common cause of the two correlated variables.Your brain does that automatically, but what about your computer? How do you make sure it doesn’t just happily (and mistakenly) report the correlation? That’s when causal inference and machine learning enter the stage, as Robert Osazuwa Ness will tell us.Robert has a PhD in statistics from Purdue University. He currently works as a Research Scientist at Microsoft Research and a founder of altdeep.ai, which teaches live cohort-based courses on advanced topics in applied modeling. As you’ll hear, his research focuses on the intersection of causal and probabilistic machine learning. Maybe that’s why I invited him on the show… Well, who knows, causal inference is very hard!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Robert's webpage: https://www.microsoft.com/en-us/research/people/robertness/Robert on Twitter: https://twitter.com/osazuwaRobert on GitHub: https://github.com/robertnessRobert on LinkedIn: https://www.linkedin.com/in/osazuwa/Do-calculus enables causal reasoning with latent variable models, Arxiv: https://arxiv.org/abs/2102.06626Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems, NeurIPS...

S1 Ep 55#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski
What’s the common point between fiction, fake news, illusions and meditation? They can all be studied with Bayesian statistics, of course!In this mind-bending episode, Dominique Makowski will for sure expand your horizon. Trained as a clinical neuropsychologist, he is currently working as a postdoc at the Clinical Brain Lab in Singapore, in which he leads the Reality Bending Team. What’s reality-bending you ask? Well, you’ll have to listen to the episode, but I can already tell you we’ll go through a journey in scientific methodology, history of art, religion, and philosophy — what else?Beyond that, Dominique tries to improve the access to advanced analysis techniques by developing open-source software and tools, like the NeuroKit Python package or the bayestestR package in R.Even better, he looks a lot like his figures of reference. Like Marcus Aurelius, he plays the piano and guitar. Like Sisyphus, he loves history of art and comparative mythology. And like Yoda, he is a wakeboard master.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Daniel Lindroth, Yoshiyuki Hamajima, Sven De Maeyer and Michael DeCrescenzo.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:To follow:Dominique's website: https://dominiquemakowski.github.io/Dominique on Twitter: https://twitter.com/Dom_MakowskiDominique on GitHub: https://github.com/DominiqueMakowskiPackages:NeuroKit -- Python Toolbox for Neurophysiological Signal Processing: https://github.com/neuropsychology/NeuroKitbayestestR -- Become a Bayesian master you will: https://easystats.github.io/bayestestR/report -- From R to your manuscript: https://easystats.github.io/report/Research:The Reality Bending...

S1 Ep 54#54 Bayes in Theoretical Ecology, with Florian Hartig
Let’s be honest: evolution is awesome! I started reading Improbable Destinies: Fate, Chance, and the Future of Evolution, by Jonathan Losos, and I’m utterly fascinated. So I’m thrilled to welcome Florian Hartig on the show. Florian is a professor of Theoretical Ecology at the University of Regensburg, Germany. His research concentrates on theory, computer simulations, statistical methods and machine learning in ecology & evolution. He is also interested in open science and open software development, and maintains, among other projects, the R packages DHARMa and BayesianTools.Among other things, we talked about approximate Bayesian computation, best practices when building models and the big pain points that remain in the Bayesian pipeline.Most importantly, Florian’s main hobbies are whitewater kayaking, snowboarding, badminton and playing the guitar.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones and Daniel Lindroth.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Florian's website: https://theoreticalecology.wordpress.com/Florian on Twitter: https://twitter.com/florianhartigFlorian on GitHub: https://github.com/florianhartigDHARMa -- Residual Diagnostics for Hierarchical Regression Models: https://cran.r-project.org/web/packages/DHARMa/index.htmlBayesianTools -- General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics: https://cran.r-project.org/web/packages/BayesianTools/index.htmlStatistical inference for stochastic simulation inference -- theory and application: https://onlinelibrary.wiley.com/doi/epdf/10.1111/j.1461-0248.2011.01640.xArviZ plot rank function:

S1 Ep 53#53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd Hudson
Get a 30% discount on Todd's book by entering the code BDABNS22 at checkout!The behavioral and neural sciences are a nerdy interest of mine, but I didn’t dedicate any episode to that topic yet. But life brings you gifts sometimes (especially around Christmas…), and here that gift is a book, Bayesian Data Analysis for the Behavioral and Neural Sciences, by Todd Hudson.Todd is a part of the faculty at New York University Grossman School of Medicine and also the New York University Tandon School of Engineering. He is a computational neuroscientist working in several areas including: early detection and grading of neurological disease; computational models of movement planning and learning; development of new computational and experimental techniques. He also co-founded Tactile Navigation Tools, which develops navigation aids for the visually impaired, and Third Eye Technologies, which develops low cost laboratory- and clinical-grade eyetracking technologies.As you’ll hear, Todd wanted his book to bypass the need for advanced mathematics normally considered a prerequisite for this type of material. Basically, he wants students to be able to write code and models and understand equations, even they are not specialized in writing those equations.We’ll also touch on some of the neural sciences examples he’s got in the book, as well as the two general algorithms he uses for model measurement and model selection.Ow, I almost forgot the most important: Todd loves beekeeping and gardening — he’s got 25 apple trees, 4 cherry trees, nectarines, figs, strawberries, etc!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Alejandro Morales, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones and Daniel Lindroth.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:30% discount on Todd's book by entering BDABNS22 at checkout:

S1 Ep 52#52 Election forecasting models in Germany, with Marcus Gross
Did I mention I like survey data, especially in the context of electoral forecasting? Probably not, as I’m a pretty shy and reserved man. Why are you laughing?? Yeah, that’s true, I’m not that shy… but I did mention my interest for electoral forecasting already!And before doing a full episode where I’ll talk about French elections (yes, that’ll come at one point), let’s talk about one of France’s neighbors — Germany. Our German friends had federal elections a few weeks ago — consequential elections, since they had the hard task of replacing Angela Merkel, after 16 years in power.To talk about this election, I invited Marcus Gross on the show, because he worked on a Bayesian forecasting model to try and predict the results of this election — who will get elected as Chancellor, by how much and with which coalition?I was delighted to ask him about how the model works, how it accounts for the different sources of uncertainty — be it polling errors, unexpected turnout or media events — and, of course, how long it takes to sample (I think you’ll be surprised by the answer). We also talked about the other challenge of this kind of work: communication — how do you communicate uncertainty effectively? How do you differentiate motivated reasoning from useful feedback? What were the most common misconceptions about the model?Marcus studied statistics in Munich and Berlin, and did a PhD on survey statistics and measurement error models in economics and archeology. He worked as a data scientist at INWT, a consulting firm with projects in different business fields as well as the public sector. Now, he is working at FlixMobility.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Alejandro Morales, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King and Aaron Jones.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:German election forecast website: https://www.wer-gewinnt-die-wahl.de/enTwitter account of electoral model: https://twitter.com/GerElectionFcstGerman election model code: https://github.com/INWTlab/lsTerm-election-forecastLBS #27 -- Modeling the US Presidential Elections, with Andrew Gelman & Merlin Heidemanns: