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Zero Variance Markov Chain Monte Carlo for Bayesian Estimators

14 December 2010

Papers citing "Zero Variance Markov Chain Monte Carlo for Bayesian Estimators"

36 / 36 papers shown

Title
Leveraging neural control variates for enhanced precision in lattice field theory Paulo F. Bedaque Hyunwoo Oh 85 6 0 13 Mar 2025
Pathwise Gradient Variance Reduction with Control Variates in Variational Inference Kenyon Ng Susan Wei BDL 48 0 0 08 Oct 2024
Doubly Adaptive Importance Sampling W. van den Boom Andrea Cremaschi Alexandre H. Thiery 59 0 0 29 Apr 2024
Control Variates for MCMC Leah South Matthew Sutton 48 0 0 12 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 135 30 0 09 Feb 2024
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality Jose H. Blanchet Haoxuan Chen Yiping Lu Lexing Ying 71 4 0 25 May 2023
Theoretical guarantees for neural control variates in MCMC Denis Belomestny Artur Goldman A. Naumov S. Samsonov BDL DRL 48 6 0 03 Apr 2023
Meta-learning Control Variates: Variance Reduction with Limited Data Z. Sun Chris J. Oates F. Briol BDL 94 9 0 08 Mar 2023
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling Rémi Leluc Franccois Portier Johan Segers Aigerim Zhuman 75 2 0 24 May 2022
Variance Reduction for Metropolis-Hastings Samplers Angelos N. Alexopoulos P. Dellaportas Michalis K. Titsias 60 2 0 04 Mar 2022
Gradient Estimation with Discrete Stein Operators Jiaxin Shi Yuhao Zhou Jessica Hwang Michalis K. Titsias Lester W. Mackey 104 23 0 19 Feb 2022
Fast compression of MCMC output Nicolas Chopin Gabriel Ducrocq 16 5 0 09 Jul 2021
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments Andreas Anastasiou Alessandro Barp F. Briol B. Ebner Robert E. Gaunt ... Qiang Liu Lester W. Mackey Chris J. Oates Gesine Reinert Yvik Swan 101 35 0 07 May 2021
Post-Processing of MCMC Leah F. South M. Riabiz Onur Teymur Chris J. Oates 95 18 0 30 Mar 2021
Variance reduction for dependent sequences with applications to Stochastic Gradient MCMC Denis Belomestny L. Iosipoi Eric Moulines A. Naumov S. Samsonov 72 6 0 16 Aug 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 113 38 0 06 Jul 2020
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization Shijing Si Chris J. Oates Andrew B. Duncan Lawrence Carin F. Briol BDL 58 21 0 12 Jun 2020
Neural Control Variates Thomas Müller Fabrice Rousselle Jan Novák A. Keller BDL 107 56 0 02 Jun 2020
Semi-Exact Control Functionals From Sard's Method Leah F. South Toni Karvonen Christopher Nemeth Mark Girolami Chris J. Oates 93 17 0 31 Jan 2020
Variance reduction for Markov chains with application to MCMC Denis Belomestny L. Iosipoi Eric Moulines A. Naumov S. Samsonov BDL 75 30 0 08 Oct 2019
Particle Methods for Stochastic Differential Equation Mixed Effects Models Imke Botha Robert Kohn Christopher C. Drovandi 51 21 0 25 Jul 2019
Kernelized Complete Conditional Stein Discrepancy Raghav Singhal Xintian Han S. Lahlou Rajesh Ranganath 87 7 0 09 Apr 2019
Variance reduction for additive functional of Markov chains via martingale representations Denis Belomestny Eric Moulines S. Samsonov 36 1 0 18 Mar 2019
Regularized Zero-Variance Control Variates Leah F. South Chris J. Oates Antonietta Mira Christopher C. Drovandi BDL 133 19 0 13 Nov 2018
A Riemann-Stein Kernel Method Alessandro Barp Christine J. Oates Emilio Porcu Mark Girolami 88 22 0 11 Oct 2018
Neural Control Variates for Variance Reduction Ruosi Wan Mingjun Zhong Haoyi Xiong Zhanxing Zhu BDL DRL 81 18 0 01 Jun 2018
Unbiased and Consistent Nested Sampling via Sequential Monte Carlo R. Salomone Leah F. South A. M. Johansen Christopher C. Drovandi Dirk P. Kroese 122 34 0 10 May 2018
Empirical Variance Minimization with Applications in Variance Reduction and Optimal Control Denis Belomestny L. Iosipoi Q. Paris Nikita Zhivotovskiy 93 8 0 13 Dec 2017
Zero Variance and Hamiltonian Monte Carlo Methods in GARCH Models Rafael S. Paixão R. Ehlers 25 1 0 20 Oct 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 91 101 0 16 Jun 2017
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 91 116 0 27 Oct 2016
Convergence Rates for a Class of Estimators Based on Stein's Method Chris J. Oates Jon Cockayne F. Briol Mark Girolami 83 57 0 10 Mar 2016
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables J. Dahlin Fredrik Lindsten J. Kronander Thomas B. Schon 86 37 0 17 Nov 2015
Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models J. Dahlin Thomas B. Schon 97 25 0 05 Nov 2015
Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods Nial Friel Antonietta Mira Chris J. Oates 107 26 0 20 Aug 2014
Split Sampling: Expectations, Normalisation and Rare Events J. Birge Changgee Chang Nicholas G. Polson 113 8 0 03 Dec 2012