Computation of Kullback–Leibler Divergence in Bayesian Networks

Kullback–Leibler divergence [Formula: see text] is the standard measure of error when we have a true probability distribution p which is approximate with probability distribution q. Its efficient computation is essential in many tasks, as in approximate computation or as a measure of error when lear...

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Detalles Bibliográficos
Autores principales: Moral, Serafín, Cano, Andrés, Gómez-Olmedo, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466032/
https://www.ncbi.nlm.nih.gov/pubmed/34573747
http://dx.doi.org/10.3390/e23091122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466032/
https://www.ncbi.nlm.nih.gov/pubmed/34573747
http://dx.doi.org/10.3390/e23091122

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