
BI NMA 04: Deep Learning Basics Panel
BI NMA 04: Deep Learning Basics Panel This is the 4th in a series of panel discussions in collaboration with Neuromatch Academy, the online computa
Audio is streamed directly from the publisher (braininspired.co) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
BI NMA 04:
Deep Learning Basics PanelThis is the 4th in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. This is the first of 3 in the deep learning series. In this episode, the panelists discuss their experiences with some basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization.
Guests
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.
- Third panel, about stochastic processes, including Bayes, decision-making, optimal control, reinforcement learning, and causality.
- 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.
Timestamps: