Evaluating probabilistic programming and fast variational Bayesian inference in phylogenetics

Recent advances in statistical machine learning techniques have led to the creation of probabilistic programming frameworks. These frameworks enable probabilistic models to be rapidly prototyped and fit to data using scalable approximation methods such as variational inference. In this work, we expl...

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Detalles Bibliográficos
Autores principales: Fourment, Mathieu, Darling, Aaron E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966998/
https://www.ncbi.nlm.nih.gov/pubmed/31976168
http://dx.doi.org/10.7717/peerj.8272

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