BI NMA 05: NLP and Generative Models Panel
from Brain Inspired Hosted by Paul Middlebrooks
BI NMA 05: 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 Brad Wyble. @bradpwyble. Kyunghyun Cho. @kchonyc. He He. @hhexiy. João Sedoc. @JoaoSedoc. 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.
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