The Connection between Bayesian Inference and Information Theory for Model Selection, Information Gain and Experimental Design

We show a link between Bayesian inference and information theory that is useful for model selection, assessment of information entropy and experimental design. We align Bayesian model evidence (BME) with relative entropy and cross entropy in order to simplify computations using prior-based (Monte Ca...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Sergey Oladyshkin, Wolfgang Nowak
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2019-11-01
Sarja:	Entropy
Aiheet:	model evidence, entropy, model selection, information entropy, bayesian experimental design, kullback–leibler divergence, markov chain monte carlo, monte carlo
Linkit:	https://www.mdpi.com/1099-4300/21/11/1081
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