A tutorial on variational Bayesian inference

被引：0

作者：

Charles W. Fox

Stephen J. Roberts

机构：

[1] University of Sheffield,Adaptive Behaviour Research Group

[2] University of Oxford,Pattern Analysis and Machine Learning Research Group, Department of Engineering Science

来源：

Artificial Intelligence Review | 2012年 / 38卷

关键词：

Variational Bayes; Mean-field; Tutorial;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This tutorial describes the mean-field variational Bayesian approximation to inference in graphical models, using modern machine learning terminology rather than statistical physics concepts. It begins by seeking to find an approximate mean-field distribution close to the target joint in the KL-divergence sense. It then derives local node updates and reviews the recent Variational Message Passing framework.

引用

页码：85 / 95

页数：10