Research ArticleAPPLIED MATHEMATICS

Machine learning of accurate energy-conserving molecular force fields

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Science Advances  05 May 2017:
Vol. 3, no. 5, e1603015
DOI: 10.1126/sciadv.1603015

Article Information

vol. 3 no. 5

Online ISSN: 
History: 
  • Received for publication December 1, 2016
  • Accepted for publication March 7, 2017

Author Information

  1. Stefan Chmiela1,
  2. Alexandre Tkatchenko2,3,*,
  3. Huziel E. Sauceda3,
  4. Igor Poltavsky2,
  5. Kristof T. Schütt1 and
  6. Klaus-Robert Müller1,4,5,*
  1. 1Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
  2. 2Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.
  3. 3Fritz-Haber-Institut der Max-Planck-Gesellschaft, 14195 Berlin, Germany.
  4. 4Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, Korea.
  5. 5Max Planck Institute for Informatics, Stuhlsatzenhausweg, 66123 Saarbrücken, Germany.
  1. *Corresponding author. Email: alexandre.tkatchenko{at}uni.lu (A.T.); klaus-robert.mueller{at}tu-berlin.de (K.-R.M.)

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