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三个采样器,一个后验:NUTS vs. Emcee vs. 嵌套采样

📌 One-Sentence Summary 对三种流行采样方法——NUTS、emcee 和嵌套采样(dynesty)在三个越来越复杂的宇宙学问题上的基准测试显示,虽然所有方法在简单的 Gaussian 式后验中表现良好,但只有 dynesty 成功捕捉到了多模态频率估算任务中的真模式和混淆。 📝 Summary 本文是一项比较研究,对象是三种采样算法:NUTS(Hamiltonian Monte

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Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

A benchmark of three popular sampling methods—NUTS, emcee, and nested sampling (dynesty)—on three increasingly complex astrophysical problems reveals that while all perform well on simple Gaussian-like posteriors, only dynesty successfully captures the true mode and aliases in a multimodal frequency estimation task.