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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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Detalhes bibliográficos
Publicado no:PeerJ
Main Authors: Fourment, Mathieu, Darling, Aaron E.
Formato: Artigo
Idioma:Inglês
Publicado em: PeerJ Inc. 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6966998/
https://ncbi.nlm.nih.gov/pubmed/31976168
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj.8272
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