English(EN) Locally adaptive step sizes for Hamiltonian Monte Carlo methods

新的HMC方法改进了复杂分布的采样

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-14 04:00

一篇新论文介绍了汉密尔顿蒙特卡洛（HMC）方法的局部自适应步长，旨在提高复杂目标分布的采样性能。该研究建立在Bou-Rabee等人先前工作的基础上，在更广泛的假设下详细介绍了自适应步长过程，并提出了替代的误差度量以减少可逆性失败拒绝。该论文还将这些自适应步长扩展到标准的HMC和Metropolis校正的动力学Langevin/广义HMC采样器，并通过一项比较不同方法的数值研究来支持。 AI

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arXiv stat.ML TIER_1 English(EN) · Jimmy Huy Tran, Tore Selland Kleppe, Nawaf Bou-Rabee · 2026-10-14 04:00

Hamiltonian Monte Carlo 方法的局部自适应步长

arXiv:2610.16506v1 Announce Type: cross Abstract: Exact reversible locally adaptive step sizes are introduced by Bou-Rabee et al. (2026) in the context of the No-U-Turn Hamiltonian Monte Carlo (HMC) sampler for the purpose of high performance HMC sampling in challenging target di…

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Hamiltonian Monte Carlo 方法的局部自适应步长

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