Machine learning for molecular simulation

Reference : Machine learning for molecular simulation


	Document type :	Scientific journals : Article
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Physics
	Focus Areas :	Physics and Materials Science
	To cite this reference:	http://hdl.handle.net/10993/45768

Title :	Machine learning for molecular simulation
Language :	English
Author, co-author :	Frank Noé []
	Tkatchenko, Alexandre [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
	Klaus-Robert Müller []
	Cecilia Clementi []
Publication date :	2020
Journal title :	Annual Review of Physical Chemistry
Publisher :	Annual Reviews
Peer reviewed :	Yes
ISSN :	0066-426X
e-ISSN :	1545-1593
City :	Palo Alto
Country :	CA
Permalink :	http://hdl.handle.net/10993/45768

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	File	Commentary	Version	Size	Access
Open access	159-ML-molecular-simulations-ARPhysChem-2020.pdf		Publisher postprint	4.21 MB	View/Open

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