A Contrastive Divergence for Combining Variational Inference and MCMC

international conference on machine learning, 2019.

Cited by: 13|Views19
EI

Abstract:

We develop a method to combine Markov chain Monte Carlo (MCMC) and variational inference (VI), leveraging the advantages of both inference approaches. Specifically, we improve the variational distribution by running a few MCMC steps. To make inference tractable, we introduce the variational contrastive divergence (VCD), a new divergence...More

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