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Particle MCMC

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Particle MCMC methods combine Sequential Monte Carlo (SMC) and MCMC methods in a principled manner, and are known to provide an excellent approach to approximate inference for state-space models in particular. We will first introduce Particle MCMC methods, and then provide a couple of view points on them with the aim of elucidating their surprisingly straightforward interpretations as particular instantiations of standard MCMC techniques.

This talk is part of the Machine Learning Reading Group @ CUED series.

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