Pseudo-extended Markov chain Monte Carlo

NeurIPS 2019 Christopher NemethFredrik LindstenMaurizio FilipponeJames Hensman

Sampling from posterior distributions using Markov chain Monte Carlo (MCMC) methods can require an exhaustive number of iterations, particularly when the posterior is multi-modal as the MCMC sampler can become trapped in a local mode for a large number of iterations. In this paper, we introduce the pseudo-extended MCMC method as a simple approach for improving the mixing of the MCMC sampler for multi-modal posterior distributions... (read more)

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