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Learning generative models of molecular dynamics
We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L(1 )reg-ularization is...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2012
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3394414/ https://ncbi.nlm.nih.gov/pubmed/22369071 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2164-13-S1-S5 |
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