BI NMA 01: Machine Learning Panel
from Brain Inspired Hosted by Paul Middlebrooks
Panelists: Athena Akrami: @AthenaAkrami. Demba Ba. Gunnar Blohm: @GunnarBlohm. Kunlin Wei. This is the first 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 model fitting, GLMs/machine learning, dimensionality reduction, and deep learning. Other panels: 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 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.
Embed this episode
No transcript yet.