BI NMA 03: Stochastic Processes Panel
Panelists: Yael Niv.@yael_nivKonrad [email protected] BI episodes:BI 027 Ioana Marinescu & Konrad Kording: Causality in Quasi-Experiments.BI 014 Konrad Kording: Regulators, Mount Up!Sam [email protected] BI episodes:BI 095 Ch
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Show Notes
Panelists:
This is the third in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. In this episode, the panelists discuss their experiences with stochastic processes, including Bayes, decision-making, optimal control, reinforcement learning, and causality.
The other panels:
- First panel, about model fitting, GLMs/machine learning, dimensionality reduction, and deep learning.
- Second panel, about linear systems, real neurons, and dynamic networks.
- Fourth panel, about basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization.
- Fifth panel, about “doing more with fewer parameters: Convnets, RNNs, attention & transformers, generative models (VAEs & GANs).
- Sixth panel, about advanced topics in deep learning: unsupervised & self-supervised learning, reinforcement learning, continual learning/causality.