"Importance Weighted Hierarchical Variational Inference"

By Artem Sobolev and Dmitry Vetrov: https://arxiv.org/abs/1905.03290

Talk: https://youtu.be/pdSu7XfGhHw

#Bayesian #MachineLearning #VariationalInference

ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python

ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python

Practical Deep Learning with Bayesian Principles
Osawa et al.: https://arxiv.org/pdf/1906.02506.pdf
#Bayesian #DeepLearning #PyTorch #VariationalInference

The Functional Neural Process
Louizos et al.: https://arxiv.org/abs/1906.08324
#ArtificialIntelligence #Bayesian #MachineLearning

Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks
Foong et al.: https://arxiv.org/abs/1909.00719
#Bayesian #NeuralNetworks #MachineLearning

BoTorch: Programmable Bayesian Optimization in PyTorch
Balandat et al.: https://arxiv.org/abs/1910.06403
Code: https://github.com/pytorch/botorch
#MachineLearning #Bayesian #PyTorch

Materials of the Summer school on Deep learning and Bayesian methods 2019
GitHub : https://github.com/bayesgroup/deepbayes-2019
#ArtificialIntelligence #DeepLearning #Bayesian

Bayesian Deep Learning Benchmarks
GitHub, by the Oxford Applied and Theoretical Machine Learning group : https://github.com/OATML/bdl-benchmarks
#Bayesian #DeepLearning #Benchmarks

Neural Density Estimation and Likelihood-free Inference
George Papamakarios : https://arxiv.org/pdf/1910.13233.pdf
#Bayesian #NeuralDensityEstimation #Inference

Bayesian Deep Learning - NeurIPS 2019 Workshop
Friday, December 13, 2019 — Vancouver Convention Center, Vancouver, Canada : http://bayesiandeeplearning.org
#bayesian #deeplearning #neurips2019