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Learning dynamic Boltzmann distributions as reduced models of spatial chemical kinetics
Finding reduced models of spatially distributed chemical reaction networks requires an estimation of which effective dynamics are relevant. We propose a machine learning approach to this coarse graining problem, where a maximum entropy approximation is constructed that evolves slowly in time. The dy...
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| Publicat a: | J Chem Phys |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
AIP Publishing LLC
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6056297/ https://ncbi.nlm.nih.gov/pubmed/30037235 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1063/1.5026403 |
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