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Lawrence Murray

2 accepted papers

2019

Parameter elimination in particle Gibbs sampling

NeurIPS 2019oral

Bayesian inference in state-space models is challenging due to high-dimensional state trajectories. A viable approach is particle Markov chain Monte Carlo (PMCMC), combining MCMC and sequential Monte Carlo to form ``exact approximations'' to otherwise-intractable MCMC methods. The performance of the…

2018

Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs

AISTATS 2018poster

We introduce a dynamic mechanism for the solution of analytically-tractable substructure in probabilistic programs, using conjugate priors and affine transformations to reduce variance in Monte Carlo estimators. For inference with Sequential Monte Carlo, this automatically yields improvements such a…

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