Pseudo extended MCMC

Chris Nemeth

MCMC algorithms are a class of exact methods used for sampling from target distributions. If the target is multimodal, MCMC algorithms often struggle to explore all of the modes of the target within a reasonable number of iterations. This issue can become even more pronounced when using efficient gradient-based samplers, such as HMC, which tend to tend to become trapped local modes.

In this talk, I'll outline how the pseudo-extended target, based on pseudo-marginal MCMC, can be used to improve the mixing of the HMC sampler by tempering the target distribution.

This is joint work with Fredrick Lindsten, Maurizio Filippone and James Hensman.

Page created on Wednesday, Nov 29, 2017