Inference on Markov random fields: methods and applications

Inference on Markov random fields: methods and applications

<p>This thesis considers the problem of performing inference on undirected graphical models with continuous state spaces. These models represent conditional independence structures that can appear in the context of Bayesian Machine Learning. In the thesis, we focus on computational methods and...

书目详细资料
主要作者:	Lienart, T
其他作者:	Doucet, A
格式:	Thesis
语言:	English
出版:	2017
主题:	Computational statistics Machine learning Bayesian statistics

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