Stochastic Expectation Propagation

12 June 2015

Jose Miguel Hernandez-Lobato

Papers citing "Stochastic Expectation Propagation"

23 / 23 papers shown

Title
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning Wenxuan Ma Xing Yan Kun Zhang UQCV 28 0 0 24 Dec 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 136 78 0 02 Oct 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard Turner FedML 19 12 0 24 Feb 2022
Approximate Inference via Clustering Qianqian Song 33 0 0 28 Nov 2021
Differentially private stochastic expectation propagation (DP-SEP) Margarita Vinaroz Mijung Park 25 1 0 25 Nov 2021
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 24 20 0 05 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 21 15 0 02 Nov 2021
Post-hoc loss-calibration for Bayesian neural networks Meet P. Vadera S. Ghosh Kenney Ng Benjamin M. Marlin UQCV BDL 43 7 0 13 Jun 2021
Infinite-dimensional gradient-based descent for alpha-divergence minimisation Kamélia Daudel Randal Douc Franccois Portier 21 17 0 20 May 2020
The $f$ -Divergence Expectation Iteration Scheme Kamélia Daudel Randal Douc Franccois Portier François Roueff 22 1 0 26 Sep 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 14 10 0 03 Jan 2019
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 27 55 0 27 Nov 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 12 46 0 05 Sep 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 24 68 0 06 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Expectation Propagation for t-Exponential Family Using Q-Algebra Futoshi Futami Issei Sato Masashi Sugiyama 18 6 0 25 May 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 49 196 0 08 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
Variational Inference via $χ$ -Upper Bound Minimization Adji Bousso Dieng Dustin Tran Rajesh Ranganath John Paisley David M. Blei BDL 83 36 0 01 Nov 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 19 1,073 0 16 Aug 2016
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation T. Bui Josiah Yan Richard Turner 24 25 0 23 May 2016
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard Turner 23 137 0 10 Nov 2015
Bayesian inference for spatio-temporal spike-and-slab priors Michael Riis Andersen Aki Vehtari Ole Winther Lars Kai Hansen 26 33 0 15 Sep 2015