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arXiv · 2312.09860

Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief Propagation

Waïss Azizian·Guillaume Baudart·Marc Lelarge
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Abstract

Exact Bayesian inference on state-space models~(SSM) is in general untractable, and unfortunately, basic Sequential Monte Carlo~(SMC) methods do not yield correct approximations for complex models. In this paper, we propose a mixed inference algorithm that computes closed-form solutions using belief propagation as much as possible, and falls back to sampling-based SMC methods when exact computations fail. This algorithm thus implements automatic Rao-Blackwellization and is even exact for Gaussian tree models.

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Waïss Azizian, Guillaume Baudart, Marc Lelarge. 2023-12-15. Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief Propagation. https://arxiv.org/abs/2312.09860

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