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Stochastic Expectation Propagation

12 June 2015

Yingzhen Li

Jose Miguel Hernandez-Lobato

Richard Turner

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Papers citing "Stochastic Expectation Propagation"

50 / 59 papers shown

Title
Fearless Stochasticity in Expectation Propagation Jonathan So Richard Turner 68 0 0 03 Jun 2024
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling Bairu Hou Yujian Liu Kaizhi Qian Jacob Andreas Shiyu Chang Yang Zhang UD UQCV PER 98 65 0 15 Nov 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models Rui Li S. T. John Arno Solin BDL 56 3 0 07 Jun 2023
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach Han Guo P. Greengard Hongyi Wang Andrew Gelman Yoon Kim Eric P. Xing FedML 75 21 0 08 Feb 2023
Variational Inference on the Final-Layer Output of Neural Networks Yadi Wei Roni Khardon BDL UQCV 91 0 0 05 Feb 2023
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning Wenxuan Ma Xing Yan Kun Zhang UQCV 66 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 231 89 0 02 Oct 2022
Differentially private partitioned variational inference Mikko A. Heikkilä Matthew Ashman S. Swaroop Richard Turner Antti Honkela FedML 63 2 0 23 Sep 2022
Image Reconstruction by Splitting Expectation Propagation Techniques from Iterative Inversion R. Aykroyd Kehinde Olobatuyi 18 0 0 25 Aug 2022
Task Agnostic and Post-hoc Unseen Distribution Detection Radhika Dua Seong-sil Yang Yixuan Li Edward Choi OODD 66 11 0 26 Jul 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 65 14 0 24 Feb 2022
Approximate Inference via Clustering Qianqian Song 66 0 0 28 Nov 2021
Differentially private stochastic expectation propagation (DP-SEP) Margarita Vinaroz Mijung Park 70 1 0 25 Nov 2021
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 93 23 0 05 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 98 16 0 02 Nov 2021
Post-hoc loss-calibration for Bayesian neural networks Meet P. Vadera S. Ghosh Kenney Ng Benjamin M. Marlin UQCV BDL 88 7 0 13 Jun 2021
Sparse Algorithms for Markovian Gaussian Processes William J. Wilkinson Arno Solin Vincent Adam 62 12 0 19 Mar 2021
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise Jannik Schmitt Stefan Roth UQCV 57 6 0 15 Mar 2021
f-Divergence Variational Inference Neng Wan Dapeng Li N. Hovakimyan 114 35 0 28 Sep 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 107 108 0 24 Aug 2020
$α$ Belief Propagation for Approximate Inference Dong Liu Minh Thành Vu Zuxing Li L. Rasmussen 45 0 0 27 Jun 2020
Infinite-dimensional gradient-based descent for alpha-divergence minimisation Kamélia Daudel Randal Douc Franccois Portier 89 18 0 20 May 2020
Quantile Propagation for Wasserstein-Approximate Gaussian Processes Rui Zhang Christian J. Walder Edwin V. Bonilla Marian-Andrei Rizoiu Lexing Xie 48 2 0 21 Dec 2019
Conditional Expectation Propagation Zheng Wang Shandian Zhe 37 11 0 27 Oct 2019
Parametric Gaussian Process Regressors M. Jankowiak Geoffrey Pleiss Jacob R. Gardner UQCV 56 5 0 16 Oct 2019
The $f$ -Divergence Expectation Iteration Scheme Kamélia Daudel Randal Douc Franccois Portier François Roueff 97 1 0 26 Sep 2019
Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods Haitao Liu Yew-Soon Ong Ziwei Yu Jianfei Cai Xiaobo Shen 66 3 0 14 Sep 2019
On the Expressiveness of Approximate Inference in Bayesian Neural Networks Andrew Y. K. Foong David R. Burt Yingzhen Li Richard Turner UQCV BDL 73 20 0 02 Sep 2019
$α$ Belief Propagation as Fully Factorized Approximation Dong Liu N. N. Moghadam L. Rasmussen Jinliang Huang Saikat Chatterjee 61 3 0 23 Aug 2019
Certainty Driven Consistency Loss on Multi-Teacher Networks for Semi-Supervised Learning Lu Liu R. Tan 82 32 0 17 Jan 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 155 10 0 03 Jan 2019
Uncertainty propagation in neural networks for sparse coding Danil Kuzin Olga Isupova Lyudmila Mihaylova BDL UQCV 34 0 0 29 Nov 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 91 56 0 27 Nov 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 146 46 0 05 Sep 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 121 70 0 06 Jun 2018
Progress & Compress: A scalable framework for continual learning Jonathan Richard Schwarz Jelena Luketina Wojciech M. Czarnecki A. Grabska-Barwinska Yee Whye Teh Razvan Pascanu R. Hadsell CLL 161 889 0 16 May 2018
Graphical Generative Adversarial Networks Chongxuan Li Max Welling Jun Zhu Bo Zhang GAN 47 36 0 10 Apr 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making Ruiyi Zhang Chunyuan Li Changyou Chen Lawrence Carin BDL UQCV 101 26 0 30 Dec 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 236 698 0 15 Nov 2017
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation Carlos Villacampa-Calvo Daniel Hernández-Lobato 78 19 0 22 Jun 2017
Expectation Propagation for t-Exponential Family Using Q-Algebra Futoshi Futami Issei Sato Masashi Sugiyama 68 6 0 25 May 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 147 197 0 08 Mar 2017
Linear Time Computation of Moments in Sum-Product Networks Haiying Zhao Geoffrey J. Gordon TPM 37 1 0 15 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 978 5,861 0 05 Dec 2016
On numerical approximation schemes for expectation propagation A. Roche 29 0 0 14 Nov 2016
Variational Inference via $χ$ -Upper Bound Minimization Adji Bousso Dieng Dustin Tran Rajesh Ranganath John Paisley David M. Blei BDL 146 35 0 01 Nov 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 142 1,096 0 16 Aug 2016
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation T. Bui Josiah Yan Richard Turner 98 25 0 23 May 2016
Patterns of Scalable Bayesian Inference E. Angelino Matthew J. Johnson Ryan P. Adams 107 87 0 16 Feb 2016
Deep Gaussian Processes for Regression using Approximate Expectation Propagation T. Bui Daniel Hernández-Lobato Yingzhen Li José Miguel Hernández-Lobato Richard Turner BDL 158 237 0 12 Feb 2016