Open AccessKernel-Based Machine Learning for Efficient Simulations of Molecular Liquids
Author(s) -
Christoph Scherer,
René Scheid,
Denis Andrienko,
Tristan Bereau
Publication year - 2020
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.9b01256
Subject(s) - covariant transformation , kernel (algebra) , ansatz , computer science , molecular dynamics , pairwise comparison , decomposition , computational science , set (abstract data type) , force field (fiction) , statistical physics , algorithm , artificial intelligence , physics , computational chemistry , mathematics , geometry , chemistry , pure mathematics , organic chemistry , quantum mechanics , programming language
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