- Author
- Year
- 2014
- Title
- Markov Chain Monte Carlo and Variational Inference: Bridging the Gap
- Event
- NIPS Workshop on Advances in Variational Inference
- Book/source title
- Accepted papers: Advances in Variational Inference: NIPS 2014 Workshop: 13 December 2014, Convention and Exhibition Center, Montreal, Canada
- Publisher
- NIPS Foundation
- Document type
- Conference contribution
- Faculty
- Faculty of Science (FNWI)
- Institute
- Informatics Institute (IVI)
- Abstract
- Recent advances in stochastic gradient variational inference have made it possible to perform variational Bayesian inference with posterior approximations containing auxiliary random variables. This enables us to explore a new synthesis of variational inference and Monte Carlo methods where we incorporate one or more steps of MCMC into our variational approximation. We describe the theoretical foundations that make this possible and show some promising first results.
- Link
- Link
- Language
- English
- Persistent Identifier
- https://hdl.handle.net/11245/1.437949
- Downloads
-
mcmcvb(Submitted manuscript)
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