Bayesian Deep Learning — ANDREW GORDON WILSON Published 2020-08-19 Download video MP4 360p Recommendations 1:57:07 Bayesian Deep Learning and Probabilistic Model Construction - ICML 2020 Tutorial 17:34 Neural Networks Pt. 2: Backpropagation Main Ideas 35:47 Telecom Silicon 2:25:52 The spelled-out intro to neural networks and backpropagation: building micrograd 1:20:30 Machine learning - Bayesian optimization and multi-armed bandits 1:07:33 Webinar: Bringing AI research to wireless communications and sensing 25:09 How Bayes Theorem works 36:15 Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning 49:34 16. Learning: Support Vector Machines 2:07:20 "Bayesian Neural Networks (with VI flavor)" by Yingzhen Li 48:52 MIT 6.S191: Evidential Deep Learning and Uncertainty 15:11 Bayes theorem, the geometry of changing beliefs 25:28 Watching Neural Networks Learn 1:19:54 [DeepBayes2019]: Day 6, Keynote Lecture 3. Uncertainty estimation in supervised learning 18:40 But what is a neural network? | Chapter 1, Deep learning 1:34:54 2. Bayesian Optimization 1:21:39 Bayesian Networks 1 - Inference | Stanford CS221: AI (Autumn 2019) Similar videos 1:15:47 Deep Learning Foundations: Andrew Wilson's Talk on How Do We Build Models That Learn and Generalize? 00:17 Old. 58:36 "Is Bayesian deep learning the most brilliant thing ever?" - a panel discussion 1:46:29 Andrew Gordon Wilson asks how do we build models that learn and generalize? 1:09:20 CBL Alumni Series: Examining Critiques in Bayesian Deep Learning 03:14 Bayesian Optimization with Gradients - NIPS 2017 More results