Speeding Up MCMC by Efficient Data Subsampling

16 April 2014

Papers citing "Speeding Up MCMC by Efficient Data Subsampling"

35 / 35 papers shown

Title
Efficient MCMC Sampling with Expensive-to-Compute and Irregular Likelihoods Conor Rosato Harvinder Lehal Simon Maskell L. Devlin Malcolm Strens 19 0 0 15 May 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 74 13 0 03 Jan 2025
Coreset Markov Chain Monte Carlo Naitong Chen Trevor Campbell 32 4 0 25 Oct 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 31 5 0 14 Jun 2023
Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data Saumajit Saha J. Bradley 27 5 0 22 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 47 4 0 21 Apr 2023
Particle Mean Field Variational Bayes Minh-Ngoc Tran Paco Tseng Robert Kohn 32 3 0 24 Mar 2023
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 28 0 0 18 Dec 2022
Non-reversible Parallel Tempering for Deep Posterior Approximation Wei Deng Qian Zhang Qi Feng F. Liang Guang Lin 26 4 0 20 Nov 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 35 15 0 01 Aug 2022
An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation Jingyi Zhang Cheng Meng Jun Yu Mengrui Zhang Wenxuan Zhong Ping Ma OT 29 12 0 31 May 2022
Bayesian inference via sparse Hamiltonian flows Na Chen Zuheng Xu Trevor Campbell 35 14 0 11 Mar 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 39 5 0 07 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 35 13 0 22 Dec 2021
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 39 26 0 20 Dec 2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 33 9 0 30 May 2021
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 33 8 0 02 Oct 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 29 60 0 22 Jun 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 32 27 0 25 Jan 2020
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 22 134 0 16 Jul 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 24 37 0 23 May 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 27 10 0 25 Mar 2019
Embarrassingly parallel MCMC using deep invertible transformations Diego Mesquita P. Blomstedt Samuel Kaski 9 18 0 11 Mar 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 23 40 0 13 Feb 2019
New models for symbolic data analysis B. Beranger Huan-xiang Lin Scott A. Sisson 21 25 0 11 Sep 2018
An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics Liangliang Wang Shijia Wang Alexandre Bouchard-Coté 18 32 0 22 Jun 2018
Scalable Bayesian Nonparametric Clustering and Classification Yang Ni Peter Muller M. Diesendruck Sinead Williamson Yitan Zhu Yuan Ji 20 26 0 07 Jun 2018
Subsampling Sequential Monte Carlo for Static Bayesian Models David Gunawan Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran 19 49 0 08 May 2018
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 29 62 0 02 Aug 2017
Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large Datasets Florian Maire Nial Friel Pierre Alquier 33 14 0 26 Jun 2017
Stochastic Bouncy Particle Sampler Ari Pakman D. Gilboa David Carlson Liam Paninski 16 32 0 03 Sep 2016
Merging MCMC Subposteriors through Gaussian-Process Approximations Christopher Nemeth Chris Sherlock 22 49 0 27 May 2016
Statistical Methods and Computing for Big Data Chun Wang Ming-Hui Chen E. Schifano Jing Wu Jun Yan 35 128 0 27 Feb 2015
Coupled MCMC with a randomized acceptance probability Geoff K. Nicholls C. Fox Alexis Muir Watt 48 41 0 30 May 2012