Machine learning of accurate energy-conserving molecular force fields

DOI DOI DOI HANDLE HANDLE ほか4件をすべて表示 一部だけ表示 研究データあり 被引用文献9件 オープンアクセス
  • Stefan Chmiela
    Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
  • Alexandre Tkatchenko
    Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.
  • Huziel E. Sauceda
    Fritz-Haber-Institut der Max-Planck-Gesellschaft, 14195 Berlin, Germany.
  • Igor Poltavsky
    Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.
  • Kristof T. Schütt
    Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
  • Klaus-Robert Müller
    Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.

書誌事項

公開日
2017-05-05
DOI
  • 10.1126/sciadv.1603015
  • 10.14279/depositonce-6849
  • 10.48550/arxiv.1611.04678
公開者
American Association for the Advancement of Science (AAAS)

説明

<jats:p>The law of energy conservation is used to develop an efficient machine learning approach to construct accurate force fields.</jats:p>

収録刊行物

  • Science Advances

    Science Advances 3 (5), e1603015-, 2017-05-05

    American Association for the Advancement of Science (AAAS)

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