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...

書誌詳細
第一著者:	Lienart, T
その他の著者:	Doucet, A
フォーマット:	学位論文
言語:	English
出版事項:	2017
主題:	Computational statistics Machine learning Bayesian statistics

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