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扩散和流形上的测地流:马尔可夫链蒙特卡罗微分几何

Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov Chain Monte Carlo
课程网址: http://videolectures.net/mlss2012_girolami_mcmc/  
主讲教师: Mark Girolami
开课单位: 格拉斯哥大学
开课时间: 2013-01-15
课程语种: 英语
中文简介:
马尔可夫链蒙特卡罗方法提供了最全面的基于模拟的工具集,可以对许多类统计模型进行推理。许多应用程序的复杂性给采样方法带来了巨大的挑战,这些方法促进了理论,方法和相关算法的持续创新。在这一系列讲座中,我们将考虑MCMC方法学的最新进展,该方法利用来自微分几何,经典非线性动力学和约束在流形上的扩散的数学思想,试图提供攻击一些最具挑战性的采样所需的工具。向统计人员提出的问题。将提供材料的逐步介绍,以确保学生掌握基本概念,并在讲座结束时能够进一步发展理论和方法。
课程简介: Markov Chain Monte Carlo methods provide the most comprehensive set of simulation based tools to enable inference over many classes of statistical models. The complexity of many applications presents an enormous challenge for sampling methods motivating continual innovation in theory, methodology and associated algorithms. In this series of lectures we will consider one recent advance in MCMC methodology, that has exploited mathematical ideas from differential geometry, classical nonlinear dynamics, and diffusions constrained on manifolds, in attempting to provide the tools required to attack some of the most challenging of sampling problems presented to statisticians. A step-by-step presentation of the material will be provided to ensure that students grasp the fundamental concepts and are able to then develop further theory and methodology at the end of the lectures.
关 键 词: 抽样; 古典微分几何; 非线性动力学
课程来源: 视频讲座网
最后编审: 2020-05-31:吴雨秋(课程编辑志愿者)
阅读次数: 58