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arXiv · 1711.00922

Binary Bouncy Particle Sampler

Ari Pakman
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Abstract

The Bouncy Particle Sampler is a novel rejection-free non-reversible sampler for differentiable probability distributions over continuous variables. We generalize the algorithm to piecewise differentiable distributions and apply it to generic binary distributions using a piecewise differentiable augmentation. We illustrate the new algorithm in a binary Markov Random Field example, and compare it to binary Hamiltonian Monte Carlo. Our results suggest that binary BPS samplers are better for easy to mix distributions.

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Ari Pakman. 2017-11-02. Binary Bouncy Particle Sampler. https://arxiv.org/abs/1711.00922

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