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...

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Bibliografische gegevens
Hoofdauteur:	Lienart, T
Andere auteurs:	Doucet, A
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	2017
Onderwerpen:	Computational statistics Machine learning Bayesian statistics

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