Probabilistic Models with Deep Neural Networks

Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference is feasible. However, developments in variational...

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Detalles Bibliográficos
Autores principales: Masegosa, Andrés R., Cabañas, Rafael, Langseth, Helge, Nielsen, Thomas D., Salmerón, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831091/
https://www.ncbi.nlm.nih.gov/pubmed/33477544
http://dx.doi.org/10.3390/e23010117

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831091/
https://www.ncbi.nlm.nih.gov/pubmed/33477544
http://dx.doi.org/10.3390/e23010117

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