1 citations · 1 across the 5 of their papers we have counts for
5 papers
A categorical account of the Metropolis-Hastings algorithm
Rob Cornish, Andi Q. Wang
Metropolis-Hastings (MH) is a foundational Markov chain Monte Carlo (MCMC) algorithm. In this paper, we ask whether it is possible to formulate and analyse MH in terms of categoric…
Analysis of Multiple-try Metropolis via Poincaré inequalities
Rocco Caprio, Sam Power, Andi Q. Wang
We study the Multiple-try Metropolis algorithm using the framework of Poincaré inequalities. We describe the Multiple-try Metropolis as an auxiliary variable implementation of a re…
Explicit convergence rates of underdamped Langevin dynamics under weighted and weak Poincaré--Lions inequalities
Giovanni Brigati, Gabriel Stoltz, Andi Q. Wang +1
We study the long-time behavior of the underdamped Langevin dynamics, in the case of so-called \emph{weak confinement}. Indeed, any distribution (in position an…
Weak Poincaré inequality comparisons for ideal and hybrid slice sampling
Sam Power, Daniel Rudolf, Björn Sprungk +1
Using the framework of weak Poincaré inequalities, we provide a general comparison between Hybrid and Ideal Slice Sampling in terms of their corresponding Dirichlet forms. In parti…
Weak Poincaré Inequalities for Markov chains: theory and applications
Christophe Andrieu, Anthony Lee, Sam Power +1
We investigate the application of Weak Poincaré Inequalities (WPI) to Markov chains to study their rates of convergence and to derive complexity bounds. At a theoretical level we i…