Variational Bayesian Approximation methods for inverse problems

被引：0

作者：

Mohammad-Djafari, Ali ^{[1
]}

机构：

[1] Univ Paris 11, Lab Signaux & Syst L2S, CNRS, UMR 8506,SUPELEC, F-91192 Gif Sur Yvette, France

来源：

2ND INTERNATIONAL WORKSHOP ON NEW COMPUTATIONAL METHODS FOR INVERSE PROBLEMS (NCMIP 2012) | 2012年 / 386卷

关键词：

D O I：

10.1088/1742-6596/386/1/012006

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

Variational Bayesian Approximation (VBA) methods are recent tools for effective Bayesian computations. In this paper, these tools are used for inverse problems where the prior models include hidden variables and where where the estimation of the hyper parameters has also to be addressed. In particular two specific prior models (Student-t and mixture of Gaussian models) are considered and details of the algorithms are given.

引用

页数：4

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