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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Dettagli Bibliografici
Autore principale:	Lienart, T
Altri autori:	Doucet, A
Natura:	Tesi
Lingua:	English
Pubblicazione:	2017
Soggetti:	Computational statistics Machine learning Bayesian statistics

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