Home
Bayesian Deep Learning and Probabilistic Model Construction - ICML 2020 Tutorial
Andrew Gordon Wilson
Jul 27, 2020
41,413 views
Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning
ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein
History of Bayesian Neural Networks (Keynote talk)
But what is a neural network? | Chapter 1, Deep learning
MIT Introduction to Deep Learning | 6.S191
Samuel Mueller | "PFNs: Use neural networks for 100x faster Bayesian predictions"
Terence Tao at IMO 2024: AI and Mathematics
Variational Inference: Foundations and Modern Methods (NIPS 2016 tutorial)
Bayesian Deep learning with 10% of the weights - Rob Romijnders
Andrew Rowan - Bayesian Deep Learning with Edward (and a trick using Dropout)
Tamara Broderick: Variational Bayes and Beyond: Bayesian Inference for Big Data (ICML 2018 tutorial)
Solving AI Uncertainty with NYU Prof. Andrew Wilson
NeurIPS 2020 Tutorial: Deep Implicit Layers
Variational Autoencoders | Generative AI Animated
Bayesian Machine Learning: A PyMC-Centric Introduction (Quan Nguyen)
Bayesian Deep Learning — ANDREW GORDON WILSON
Yarin Gal -. Bayesian Deep Learning
First lecture on Bayesian Deep Learning and Uncertainty Quantification
MIT 6.S191: Evidential Deep Learning and Uncertainty
Harvard Professor Explains Algorithms in 5 Levels of Difficulty | WIRED