Control Variates for MCMC
Methodology
2025-11-21 v2 Computation
Abstract
This chapter describes several control variate methods for improving estimates of expectations from MCMC.
Cite
@article{arxiv.2402.07349,
title = {Control Variates for MCMC},
author = {Leah South and Matthew Sutton},
journal= {arXiv preprint arXiv:2402.07349},
year = {2025}
}
Comments
To appear in the second edition of the Handbook of MCMC. Associated code available at https://github.com/LeahPrice/CVBookChapter/
Related papers
View all related →
Computation · Statistics
Notes on Using Control Variates for Estimation with Reversible MCMC Samplers
Ioannis Kontoyiannis, Petros Dellaportas
2010-05-05
Statistics Theory · Mathematics
Control variates for variance-reduced ratio of means estimators
Louison Bocquet-Nouaille, Jérôme Morio, Benjamin Bobbia
2025-11-10
Computation · Statistics
Control Variates for Reversible MCMC Samplers
Petros Dellaportas, Ioannis Kontoyiannis
2010-08-10
Machine Learning · Statistics
Neural Control Variates for Variance Reduction
Ruosi Wan, Mingjun Zhong, Haoyi Xiong, Zhanxing Zhu
2019-10-16
Probability · Mathematics
A control variate method driven by diffusion approximation
Josselin Garnier, Laurent Mertz
2020-08-10
Machine Learning · Statistics
A Framework for Sample Efficient Interval Estimation with Control Variates
Shengjia Zhao, Christopher Yeh, Stefano Ermon
2020-06-19
Statistics Theory · Mathematics
Multilevel Surrogate-based Control Variates
Mohamed Reda El Amri, Paul Mycek, Sophie Ricci, Matthias De Lozzo
2024-06-21
Computational Finance · Quantitative Finance
Some Control Variates for exotic options
JC Ndogmo
2008-12-10
Computational Engineering, Finance, and Science · Computer Science
A Control Variate Approach for Improving Efficiency of Ensemble Monte Carlo
T. Borogovac, F. J. Alexander, P. Vakili
2008-09-25
Machine Learning · Statistics
Reducing the error of Monte Carlo Algorithms by Learning Control Variates
Brendan D. Tracey, David H. Wolpert
2016-06-08
Numerical Analysis · Mathematics
Multi-scale variance reduction methods based on multiple control variates for kinetic equations with uncertainties
Giacomo Dimarco, Lorenzo Pareschi
2018-12-14
Methodology · Statistics
Diffusion approximations and control variates for MCMC
Nicolas Brosse, Alain Durmus, Sean Meyn, Eric Moulines +1
2019-07-09
Machine Learning · Computer Science
Using Large Ensembles of Control Variates for Variational Inference
Tomas Geffner, Justin Domke
2020-10-23
Methodology · Statistics
Vector-Valued Control Variates
Zhuo Sun, Alessandro Barp, François-Xavier Briol
2023-06-08
Statistics Theory · Mathematics
Theoretical guarantees for neural control variates in MCMC
Denis Belomestny, Artur Goldman, Alexey Naumov, Sergey Samsonov
2024-10-29
Methodology · Statistics
Multilevel Control Functional
Kaiyu Li, Yiming Yang, Xiaoyuan Cheng, Yi He +1
2026-02-27
Computation · Statistics
On the Optimization of Approximate Control Variates with Parametrically Defined Estimators
Geoffrey F. Bomarito, Patrick E. Leser, James E. Warner, William P. Leser
2020-12-07
Numerical Analysis · Mathematics
Multi-scale control variate methods for uncertainty quantification in kinetic equations
Giacomo Dimarco, Lorenzo Pareschi
2019-05-01
Numerical Analysis · Mathematics
Coupling Control Variates for Markov Chain Monte Carlo
Jonathan B. Goodman, Kevin K. Lin
2015-05-13
Machine Learning · Statistics
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Shijing Si, Chris. J. Oates, Andrew B. Duncan, Lawrence Carin +1
2021-07-22
Statistics Theory · Mathematics
Control variates and Rao-Blackwellization for deterministic sweep Markov chains
Stephen Berg, Jun Zhu, Murray K. Clayton
2019-12-17
Methodology · Statistics
Controlled stratification for quantile estimation
Claire Cannamela, Josselin Garnier, Bertrand Iooss
2009-01-27
Computation · Statistics
Quantifying uncertain system outputs via the multi-level Monte Carlo method -- distribution and robustness measures
Quentin Ayoul-Guilmard, Sundar Ganesh, Sebastian Krumscheid, Fabio Nobile
2023-05-23
Computation · Statistics
On Using Control Variates with Stochastic Approximation for Variational Bayes and its Connection to Stochastic Linear Regression
Tim Salimans, David A. Knowles
2014-01-14
Statistics Theory · Mathematics
Variance reduction for dependent sequences with applications to Stochastic Gradient MCMC
D. Belomestny, L. Iosipoi, E. Moulines, A. Naumov +1
2020-08-18