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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 expensive...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372922/ https://www.ncbi.nlm.nih.gov/pubmed/34358223 http://dx.doi.org/10.1371/journal.pcbi.1009275 |