Stochastic gradient Markov chain Monte Carlo

16 July 2019

Papers citing "Stochastic gradient Markov chain Monte Carlo"

19 / 19 papers shown

Title
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 82 3 0 28 Jan 2025
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics Daniel Paulin P. Whalley Neil K. Chada B. Leimkuhler BDL 43 4 0 14 Oct 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 62 1 0 31 May 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics Lorenzo Mauri Giacomo Zanella 30 3 0 14 May 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 29 0 0 05 Mar 2024
Coreset Markov Chain Monte Carlo Naitong Chen Trevor Campbell 21 4 0 25 Oct 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 23 5 0 14 Jun 2023
Gibbs Sampling the Posterior of Neural Networks Giovanni Piccioli Emanuele Troiani Lenka Zdeborová 36 2 0 05 Jun 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 36 4 0 21 Apr 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner J. Zavadlav 27 21 0 15 Dec 2022
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification Xue Li Wei Shen Denis Xavier Charles UQCV EDL 30 3 0 12 Sep 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 22 15 0 01 Aug 2022
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 17 8 0 06 Dec 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 32 1,109 0 07 Jul 2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 27 9 0 30 May 2021
A hybrid Gibbs sampler for edge-preserving tomographic reconstruction with uncertain view angles Felipe Uribe Johnathan M. Bardsley Yiqiu Dong P. Hansen N. A. B. Riis 11 10 0 14 Apr 2021
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 86 222 0 06 Mar 2017
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 58 231 0 11 Jul 2016
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 34 42 0 16 Oct 2015