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...

Полное описание

Библиографические подробности
Главный автор:	Lienart, T
Другие авторы:	Doucet, A
Формат:	Диссертация
Язык:	English
Опубликовано:	2017
Предметы:	Computational statistics Machine learning Bayesian statistics

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