Probabilistic Methods · Variational Inference

TitleAuthors
Approximate Inference Turns Deep Networks into Gaussian ProcessesMohammad Emtiyaz Khan · Alexander Immer · Ehsan Abedi · Maciej Korzepa
Copula-like Variational InferenceMarcel Hirt · Petros Dellaportas · Alain Durmus
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior ApproximationJustin Domke · Daniel Sheldon
Importance Weighted Hierarchical Variational InferenceArtem Sobolev · Dmitry Vetrov
Practical Deep Learning with Bayesian PrinciplesKazuki Osawa · Siddharth Swaroop · Mohammad Emtiyaz Khan · Anirudh Jain · Runa Eschenhagen · Richard E Turner · Rio Yokota
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete DataDominik Linzner · Michael Schmidt · Heinz Koeppl
Universal Boosting Variational InferenceTrevor Campbell · Xinglong Li
Variational Bayes under Model MisspecificationYixin Wang · David Blei
Variational Bayesian Decision-making for Continuous UtilitiesTomasz Kuśmierczyk · Joseph Sakaya · Arto Klami
Variational Bayesian Optimal Experimental DesignAdam Foster · Martin Jankowiak · Elias Bingham · Paul Horsfall · Yee Whye Teh · Thomas Rainforth · Noah Goodman
A New Distribution on the Simplex with Auto-Encoding ApplicationsAndrew Stirn · Tony Jebara · David Knowles
Bayesian Layers: A Module for Neural Network UncertaintyDustin Tran · Mike Dusenberry · Mark van der Wilk · Danijar Hafner
Streaming Bayesian Inference for Crowdsourced ClassificationEdoardo Manino · Long Tran-Thanh · Nicholas Jennings
Learning Hawkes Processes from a handful of eventsFarnood Salehi · William Trouleau · Matthias Grossglauser · Patrick Thiran
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High DimensionsPeng Chen · Keyi Wu · Joshua Chen · Tom O'Leary-Roseberry · Omar Ghattas
Provable Gradient Variance Guarantees for Black-Box Variational InferenceJustin Domke
Semi-Implicit Graph Variational Auto-EncodersArman Hasanzadeh · Ehsan Hajiramezanali · Krishna Narayanan · Nick Duffield · Mingyuan Zhou · Xiaoning Qian
Sparse Variational Inference: Bayesian Coresets from ScratchTrevor Campbell · Boyan Beronov
Stein Variational Gradient Descent With Matrix-Valued KernelsDilin Wang · Ziyang Tang · Chandrajit Bajaj · Qiang Liu
Tensor Monte Carlo: Particle Methods for the GPU eraLaurence Aitchison
The Thermodynamic Variational ObjectiveVaden Masrani · Tuan Anh Le · Frank Wood