[DeepBayes2018]: Day 2, lecture 2. Scalable Bayesian methods

[DeepBayes2018]: Day 6, Lecture 2. Sparse variational dropout and variance networksПодробнее

[DeepBayes2018]: Day 5, Lecture 5. Stochastic Markov chain Monte CarloПодробнее

[DeepBayes2018]: Day 2, lecture 3. Variational autoencodersПодробнее

Bayesian Methods Lecture 2 2Подробнее

[DeepBayes2018]: Day 1, practical session 2. Bayesian reasoningПодробнее

[DeepBayes2018]: Day 3, Invited talk 1. Advanced methods of variational inferenceПодробнее

Lecture 8: Intro to Bayesian Methods (part 2)Подробнее

[DeepBayes2018]: Day 5, Practical session 2. Bayesian optimizationПодробнее

Bayesian Methods Lecture 2 1Подробнее

Stats 502 Video 2 Bayesian IntervalПодробнее

Scalable Bayesian Deep Learning with Modern Laplace ApproximationsПодробнее

2007 Methods Lecture, Guido Imben, "Bayesian Inference"Подробнее

102C Lesson 1-3 Bayesian inference with a posterior distribution (Lecture 2)Подробнее

Bayesian data interpretation with large scale cosmological (...) - Jasche - Workshop 2 - CEB T3 2018Подробнее

Lecture 2 Bayesian InferenceПодробнее

Rémi Bardenet: A tutorial on Bayesian machine learning: what, why and how - lecture 2Подробнее

Bayesian approaches for (bulk and single-cell) RNA-seq data (2 of 4)Подробнее

Scalable Bayesian Inference - NeurIPS 2018Подробнее