207 citations · 565 across the 24 of their papers we have counts for
21 papers · 1 filter
Resampling in conditional SMC algorithms
Axel Finke, Adam M. Johansen, Anthony Lee +1
Conditional sequential Monte Carlo (CSMC) algorithms arise in particle Markov chain Monte Carlo and a number of related settings. As in standard sequential Monte Carlo (SMC) algori…
Solving the Poisson equation using coupled Markov chains
Randal Douc, Pierre E. Jacob, Anthony Lee +1
This article shows how coupled Markov chains that meet exactly after a random number of iterations can be used to generate unbiased estimators of the solutions of the Poisson equat…
Comparison of Markov chains via weak Poincaré inequalities with application to pseudo-marginal MCMC
Christophe Andrieu, Anthony Lee, Sam Power +1
We investigate the use of a certain class of functional inequalities known as weak Poincaré inequalities to bound convergence of Markov chains to equilibrium. We show that this ena…
A general perspective on the Metropolis-Hastings kernel
Christophe Andrieu, Anthony Lee, Sam Livingstone
Since its inception the Metropolis-Hastings kernel has been applied in sophisticated ways to address ever more challenging and diverse sampling problems. Its success stems from the…
Accelerating sequential Monte Carlo with surrogate likelihoods
Joshua J Bon, Anthony Lee, Christopher Drovandi
Delayed-acceptance is a technique for reducing computational effort for Bayesian models with expensive likelihoods. Using a delayed-acceptance kernel for Markov chain Monte Carlo c…
Global consensus Monte Carlo
Lewis J. Rendell, Adam M. Johansen, Anthony Lee +1
To conduct Bayesian inference with large data sets, it is often convenient or necessary to distribute the data across multiple machines. We consider a likelihood function expressed…