SiGMoiD: A super-statistical generative model for binary data.
In modern computational biology, there is great interest in building probabilistic models to describe collections of a large number of co-varying binary variables. However, current approaches to build generative models rely on modelers' identification of constraints and are computationally expe...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Public Library of Science (PLoS)
2021
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| Accès en ligne: | https://doaj.org/article/d7f5ee881f6c4f3ba30cfda4a58586f1 |
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