SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Reference : SchNet: A continuous-filter convolutional neural network for modeling quantum interactions


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Physics and Materials Science; Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/34379

Title :	SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Language :	English
Author, co-author :	Schütt, Kristof T. []
	Kindermans, P. J. []
	Sauceda, Huziel E. []
	Chmiela, Stefan []
	Tkatchenko, Alexandre [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Physics and Materials Science Research Unit >]
	Müller, Klaus R. []
Publication date :	Dec-2017
Main document title :	31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA
Pages :	1-11
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA
Event date :	05-12-2017
Permalink :	http://hdl.handle.net/10993/34379

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	File	Commentary	Version	Size	Access
Open access	113-SchNet-NIPS-2017.pdf		Publisher postprint	9.49 MB	View/Open

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