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Continuous-time MCMC, Paul Fearnhead (CSSS Seminar, 3/6/2019)

Posted: 3/4/2019 (Local Events)

Continuous-time MCMC

Paul Fearnhead

Professor, Departments of Statistics, Lancaster University

Recently, there have been conceptually novel developments in Monte Carlo methods through the introduction of new MCMC algorithms which are based on continuous-time, rather than discrete-time, Markov processes. These show promise for scalable Bayesian Analysis: they naturally have non-reversible dynamics which enable them to mix faster in high-dimensional settings; sometimes they can be implemented in a way that requires access to only a small number of data points at each iteration, and yet still sample from the true posterior; and they automatically take account of sparsity in the dependence structure. This talk will give an overview of the recent work in this area.

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Date: 03/06/2019

Time: 12:30–1:30 PM

Location: Savery (SAV) 409