Fetching the paper…
Reading the bibliography…
A new methodology is presented for the construction of control variates to reduce the variance of additive functionals of Markov Chain Monte Carlo (MCMC) samplers.
Calculus: Multi Variable Calculus and Linear Algebra, with Applications to Differential Equations and Probability
Tom M Apostol · 1969
Earlier work this paper cites.
Correlation functions and computer simulations
G. Parisi · 1981
Earlier work this paper cites.
On classical limit theorems for diffusions
R. N. Bhattacharya · 1982
Earlier work this paper cites.
Tutorial in pattern theory
U. Grenander · 1983
Earlier work this paper cites.
Stability of Markovian processes. III. Foster-Lyapunov criteria for continuous-time processes
Sean P. Meyn and R. L. Tweedie · 1993
Earlier work this paper cites.
Representations of knowledge in complex systems
U. Grenander and M. I. Miller · 1994
Earlier work this paper cites.
A Liapunov bound for solutions of the Poisson equation
Peter W. Glynn and Sean P. Meyn · 1996
Earlier work this paper cites.
Exponential convergence of Langevin distributions and their discrete approximations
G. O. Roberts and R. L. Tweedie · 1996
Earlier work this paper cites.
Variance reduction via an approximating markov process
Shane G Henderson · 1997
Earlier work this paper cites.
Weak convergence and optimal scaling of random walk Metropolis algorithms
G. O. Roberts, A. Gelman, and W. R. Gilks · 1997
Earlier work this paper cites.
Optimal scaling of discrete approximations to Langevin diffusions
Gareth O. Roberts and Jeffrey S. Rosenthal · 1998
Earlier work this paper cites.
Zero-variance principle for Monte Carlo algorithms
Roland Assaraf and Michel Caffarel · 1999
Earlier work this paper cites.
Adaptive estimation of a quadratic functional by model selection
B. Laurent and P. Massart · 2000
Earlier work this paper cites.
Monte Carlo statistical methods
C. P. Robert and G. Casella · 2004
Earlier work this paper cites.
Bayesian core: a practical approach to computational Bayesian statistics
Jean-Michel Marin and Christian Robert · 2007
Cited alongside, same era.
Monte Carlo strategies in scientific computing
Jun S Liu · 2008
Cited alongside, same era.
Control techniques for complex networks
Sean Meyn · 2008
Cited alongside, same era.
Markov Chains and Stochastic Stability
S. Meyn and R. Tweedie · 2009
Cited alongside, same era.
Batch means and spectral variance estimators in Markov chain Monte Carlo
James M. Flegal and Galin L. Jones · 2010
Cited alongside, same era.
Chernoff-type bounds for the Gaussian error function
S. H. Chang, P. C. Cosman, and L. B. Milstein · 2011
Cited alongside, same era.
Reflection couplings and contraction rates for diffusions
Andreas Eberle · 2015
Later among the works it cites.
Error analysis of the transport properties of Metropolized schemes
Max Fathi, Ahmed-Amine Homman, and Gabriel Stoltz · 2015
Later among the works it cites.
Weak backward error analysis for overdamped Langevin processes
M. Kopec · 2015
Later among the works it cites.
Control functionals for Monte Carlo integration
Chris J. Oates, Mark Girolami, and Nicolas Chopin · 2016
Later among the works it cites.
Nonasymptotic convergence analysis for the unadjusted Langevin algorithm
Alain Durmus and Éric Moulines · 2017
Later among the works it cites.
On the convergence of Hamiltonian Monte Carlo
A. Durmus, E. Moulines, and E. Saksman · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Central limit theorems for additive functionals of ergodic Markov diffusions processes
Patrick Cattiaux, Djalil Chafaı, and Arnaud Guillin · 2012
Cited alongside, same era.
Control variates for estimation based on reversible Markov chain Monte Carlo samplers
P. Dellaportas and I. Kontoyiannis · 2012
Cited alongside, same era.
Notes on the implicit function theorem
KC Border · 2013
Cited alongside, same era.
Zero variance Markov chain Monte Carlo for Bayesian estimators
Antonietta Mira, Reza Solgi, and Daniele Imparato · 2013
Cited alongside, same era.
Analysis and geometry of Markov diffusion operators
D. Bakry, I. Gentil, and M. Ledoux · 2014
Cited alongside, same era.
Bayesian data analysis
Andrew Gelman, John B Carlin, Hal S Stern, David B Dunson, Aki Vehtari, and Donald B Rubin · 2014
Cited alongside, same era.
Later among the works it cites.
Simulation and the Monte Carlo method
R. Y. Rubinstein and D. P. Kroese · 2017
Later among the works it cites.
Variance reduction in monte carlo estimators via empirical variance minimization
D. V. Belomestny, L. S. Iosipoi, and N. K. Zhivotovskiy · 2018
Closest in time.
Markov chains
R. Douc, E. Moulines, P. Priouret, and P. Soulier · 2018
Closest in time.
Quantitative contraction rates for markov chains on general state spaces
A. Eberle and M. B. Majka · 2018
Closest in time.
Regularised zero-variance control variates
Leah F South, Antonietta Mira, and Christopher Drovandi · 2018
Closest in time.
Neural Control Variates for Variance Reduction
Zhanxing Zhu, Ruosi Wan, and Mingjun Zhong · 2018
Closest in time.
Convergence of diffusions and their discretizations:from continuous to discrete processes and back
V. De Bortoli and A. Durmus · 2019
Closest in time.