Amortised Inference in Bayesian Neural Networks

6 September 2023

Papers citing "Amortised Inference in Bayesian Neural Networks"

21 / 21 papers shown

Title
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning Matthew Ashman Chao Ma Agrin Hilmkil Joel Jennings Cheng Zhang CML AI4CE 85 10 0 22 Mar 2023
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 123 58 0 23 Feb 2022
Scalable Gaussian Process Variational Autoencoders Metod Jazbec Matthew Ashman Vincent Fortuin Michael Pearce Stephan Mandt Gunnar Rätsch DRL BDL 57 29 0 26 Oct 2020
Sparse Gaussian Process Variational Autoencoders Matthew Ashman Jonathan So Will Tebbutt Vincent Fortuin Michael Pearce Richard Turner 104 35 0 20 Oct 2020
Notes on the Behavior of MC Dropout Francesco Verdoja Ville Kyrki UQCV OOD BDL 48 37 0 06 Aug 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 68 215 0 14 May 2020
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 80 168 0 29 Oct 2019
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes James Requeima Jonathan Gordon J. Bronskill Sebastian Nowozin Richard Turner 69 242 0 18 Jun 2019
Conditional Neural Processes M. Garnelo Dan Rosenbaum Chris J. Maddison Tiago Ramalho D. Saxton Murray Shanahan Yee Whye Teh Danilo Jimenez Rezende S. M. Ali Eslami UQCV BDL 88 705 0 04 Jul 2018
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 288 503 0 11 Jun 2018
Meta-Learning Probabilistic Inference For Prediction Jonathan Gordon J. Bronskill Matthias Bauer Sebastian Nowozin Richard Turner BDL 120 265 0 24 May 2018
Variational Message Passing with Structured Inference Networks Wu Lin Nicolas Hubacher Mohammad Emtiyaz Khan BDL 67 54 0 15 Mar 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 829 11,943 0 09 Mar 2017
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 62 257 0 15 Mar 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 293 4,807 0 04 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 854 9,346 0 06 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 318 4,196 0 21 May 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,426 0 28 Nov 2014
Expectation Propagation for approximate Bayesian inference T. Minka 137 1,909 0 10 Jan 2013
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 171 4,309 0 18 Nov 2011