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An Exact Auxiliary Variable Gibbs Sampler for a Class of Diffusions
Qi Wang, Vinayak Rao, Yee Whye Teh
Stochastic differential equations (SDEs) or diffusions are continuous-valued continuous-time stochastic processes widely used in the applied and mathematical sciences. Simulating p…
Inference Trees: Adaptive Inference with Exploration
Tom Rainforth, Yuan Zhou, Xiaoyu Lu +4
We introduce inference trees (ITs), a new class of inference methods that build on ideas from Monte Carlo tree search to perform adaptive sampling in a manner that balances explora…
A hybrid sampler for Poisson-Kingman mixture models
Maria Lomeli, Stefano Favaro, Yee Whye Teh
This paper concerns the introduction of a new Markov Chain Monte Carlo scheme for posterior sampling in Bayesian nonparametric mixture models with priors that belong to the general…
Expectation Particle Belief Propagation
Thibaut Lienart, Yee Whye Teh, Arnaud Doucet
We propose an original particle-based implementation of the Loopy Belief Propagation (LPB) algorithm for pairwise Markov Random Fields (MRF) on a continuous state space. The algori…
Asynchronous Anytime Sequential Monte Carlo
Brooks Paige, Frank Wood, Arnaud Doucet +1
We introduce a new sequential Monte Carlo algorithm we call the particle cascade. The particle cascade is an asynchronous, anytime alternative to traditional particle filtering alg…
A marginal sampler for -Stable Poisson-Kingman mixture models
María Lomelí, Stefano Favaro, Yee Whye Teh
We investigate the class of -stable Poisson-Kingman random probability measures (RPMs) in the context of Bayesian nonparametric mixture modeling. This is a large class of discre…