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English(EN) An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning

新论文介绍用于科学推断的模拟基经验贝叶斯

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新论文介绍了模拟基经验贝叶斯（SBEB），这是一种在似然仅可通过模拟器获得的条件下，对相关潜在变量进行同步推断的方法。第一篇论文《模拟基经验贝叶斯》通过使用观测数据、模拟器样本和摊销推断网络，详细介绍了SBEB在没有显式密度的情况下计算EB估计值的方法。第二篇论文《机器学习中的贝叶斯和频率派模拟基推断简介》概述了基于机器学习的SBI的贝叶斯和频率派框架，并重点介绍了它们在参数估计、经验贝叶斯和展开任务中的应用。 AI

影响 引入了使用机器学习进行科学推断的新方法，有可能提高复杂模拟的准确性。

排序理由 两篇在arXiv上发表的学术论文，介绍了模拟基经验贝叶斯。

在 arXiv stat.ML 阅读 →

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新论文介绍用于科学推断的模拟基经验贝叶斯

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两篇在arXiv上发表的学术论文，介绍了模拟基经验贝叶斯。
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报道来源 [2]

  1. arXiv stat.ML TIER_1 English(EN) · Xinwei Shen, Diana Cai, Cheng Zhang, David M. Blei ·

    基于仿真的经验贝叶斯

    arXiv:2607.21843v1 Announce Type: new Abstract: Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tractable. In many scientific applications, however, the likelihood is available only th…

  2. arXiv stat.ML TIER_1 English(EN) · Maximilian Dax, Theo Heimel, Gilles Louppe ·

    机器学习中的贝叶斯与频率派模拟基推理导论

    arXiv:2607.21702v1 Announce Type: cross Abstract: Simulation-based inference (SBI) with machine learning is an increasingly important tool for solving inverse problems in science and engineering, including parameter inference and the inversion of detector effects. We provide an o…

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