Distributed Bayesian Learning with Stochastic Natural-gradient
Expectation Propagation and the Posterior Server

Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server

31 December 2015

Leonard Hasenclever

Thibaut Lienart

Sebastian J. Vollmer

Balaji Lakshminarayanan

Charles Blundell

Papers citing "Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server"

18 / 18 papers shown

Title
Bayesian Active Learning for Multi-Criteria Comparative Judgement in Educational Assessment Andy Gray Alma A. M. Rahat Tom Crick Stephen Lindsay ELM 46 1 0 01 Mar 2025
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 96 1 0 25 Nov 2024
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 29 2 0 26 Mar 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
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Model Fusion with Kullback--Leibler Divergence Sebastian Claici Mikhail Yurochkin S. Ghosh Justin Solomon FedML MoMe 29 33 0 13 Jul 2020
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 32 37 0 23 May 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
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 268 0 13 Jun 2018
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization Yanshuai Cao G. Ding Kry Yik-Chau Lui Ruitong Huang GAN 18 19 0 09 May 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 28 32 0 26 Sep 2017
Warped Riemannian metrics for location-scale models Salem Said Lionel Bombrun Y. Berthoumieu 43 15 0 22 Jul 2017
Element-centric clustering comparison unifies overlaps and hierarchy Alexander J. Gates Ian B. Wood W. Hetrick Yong-Yeol Ahn 9 89 0 19 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 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
Stochastic Gradient MCMC with Stale Gradients Changyou Chen Nan Ding Chunyuan Li Yizhe Zhang Lawrence Carin BDL 35 23 0 21 Oct 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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015