Article (Scientific journals)
Improving molecular force fields across configurational space by combining supervised and unsupervised machine learning
Cordeiro Fonseca, Gregory; Poltavskyi, Igor; Vassilev Galindo, Valentin et al.
2021In Journal of Chemical Physics
Peer reviewed
 

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Disciplines :
Physics
Author, co-author :
Cordeiro Fonseca, Gregory ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
Poltavskyi, Igor ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
Vassilev Galindo, Valentin ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
Tkatchenko, Alexandre ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
External co-authors :
yes
Language :
English
Title :
Improving molecular force fields across configurational space by combining supervised and unsupervised machine learning
Publication date :
22 March 2021
Journal title :
Journal of Chemical Physics
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 10 January 2022

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