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arXiv · 2501.05908

MCMC for multi-modal distributions

Krzysztof Łatuszyński·Matthew T. Moores·Timothée Stumpf-Fétizon
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Abstract

We explain the fundamental challenges of sampling from multimodal distributions, particularly for high-dimensional problems. We present the major types of MCMC algorithms that are designed for this purpose, including parallel tempering, mode jumping and Wang-Landau, as well as several state-of-the-art approaches that have recently been proposed. We demonstrate these methods using both synthetic and real-world examples of multimodal distributions with discrete or continuous state spaces.

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Krzysztof Łatuszyński, Matthew T. Moores, Timothée Stumpf-Fétizon. 2025-01-10. MCMC for multi-modal distributions. https://arxiv.org/abs/2501.05908

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