NLP and Generative Models Panel

This is the 5th in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. This is the 2nd of 3 in the deep learning series. In this episode, the panelists discuss their experiences “doing more with fewer parameters: Convnets, RNNs, attention & transformers, generative models (VAEs & GANs).

Panelists

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.
Fourth panel, about some basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization.
Sixth panel, about advanced topics in deep learning: unsupervised & self-supervised learning, reinforcement learning, continual learning/causality.

Show Notes

BI NMA 05:

NLP and Generative Models Panel

Panelists

Other Episodes

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BI 012 Niko Kriegeskorte: Black Box, White Box

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BI NMA 03: Stochastic Processes Panel

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BI 033 Federico Turkheimer: Weak Versus Strong Emergence