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Dave Blei: "Black Box Variational Inference"
PROBPROG Conference
Nov 1, 2018
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Dan Roy: "Algorithmic Barriers to Representing Conditional Independence"
Stuart Russell: "Probabilistic programming and AI"
Austin Rochford | Variational Inference in Python
MLSS 2019 David Blei: Variational Inference: Foundations and Innovations (Part 1)
Variational Inference: Foundations and Modern Methods (NIPS 2016 tutorial)
Terence Tao at IMO 2024: AI and Mathematics
Variational Inference | Evidence Lower Bound (ELBO) | Intuition & Visualization
History of Bayesian Neural Networks (Keynote talk)
Prof. David Blei - Probabilistic Topic Models and User Behavior
Fast Quantification of Uncertainty and Robustness with Variational Bayes
The Grandfather Of Generative Models
David Blei Variational Inference Foundations and Innovations Part 2
Variational Inference Lecture I|Probabilistic Modelling|Machine Learning
Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning
Andrew Rowan - Bayesian Deep Learning with Edward (and a trick using Dropout)
Nonparametric Bayesian Methods: Models, Algorithms, and Applications I
Yee Whye Teh: On Bayesian Deep Learning and Deep Bayesian Learning (NIPS 2017 Keynote)
Think Fast, Talk Smart: Communication Techniques
Limits of Logic: The Gödel Legacy
Bayesian Deep Learning and Probabilistic Model Construction - ICML 2020 Tutorial