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Learning moment closure in reaction-diffusion systems with spatial dynamic Boltzmann distributions

Many physical systems are described by probability distributions that evolve in both time and space. Modeling these systems is often challenging due to their large state space and analytically intractable or computationally expensive dynamics. To address these problems, we study a machine-learning a...

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Veröffentlicht in:Phys Rev E
Hauptverfasser: Ernst, Oliver K., Bartol, Thomas M., Sejnowski, Terrence J., Mjolsness, Eric
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2019
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6852890/
https://ncbi.nlm.nih.gov/pubmed/31330605
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1103/PhysRevE.99.063315
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