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Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids

[Image: see text] Current machine learning (ML) models aimed at learning force fields are plagued by their high computational cost at every integration time step. We describe a number of practical and computationally efficient strategies to parametrize traditional force fields for molecular liquids...

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Detalles Bibliográficos
Autores principales: Scherer, Christoph, Scheid, René, Andrienko, Denis, Bereau, Tristan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304872/
https://www.ncbi.nlm.nih.gov/pubmed/32282206
http://dx.doi.org/10.1021/acs.jctc.9b01256