arXiv Machine Learning August 11, 2026 By Qian-Rui Lee, Daw-Wei Wang

Efficient identification of critical regions via Flow Matching-based Monte Carlo initialization

Read the original on arXiv Machine Learning →

arXiv:2508. 15318v5 Announce Type: replace-cross Abstract: Markov chain Monte Carlo (MCMC) is a standard tool for studying many-body systems, but its practical cost can become substantial, especially when simulations must be repeated across temperatures and lattice sizes or near transition regions where equilibration becomes increasingly difficult.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

diffusion

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multimodal benchmarks

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diffusion benchmarks

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fine-tuning

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diffusion multimodal

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Stable Global Weighting of Flow Mixtures using Simplex Exponential Moving Average

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