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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2019-12-01
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| Series: | PeerJ |
| Subjects: | |
| Online Access: | https://peerj.com/articles/8272.pdf |