Molecular Dynamics Ex Machina: Successes and Challenges

Presentations

• Smart Sampling for Chemical Property Landscapes with BOSS

  Invited

  March 3, 2020, 8:00 AM – March 3, 2020, 8:36 AM

  Presenters

  • Milica Todorovic

    • Department of Applied Physics, Aalto University
    • Aalto University

  Authors

  • Milica Todorovic

    • Department of Applied Physics, Aalto University
    • Aalto University

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• Construction and simulation proofs of reliable high-dimensional neural network atomic potentials

  Invited

  March 3, 2020, 8:36 AM – March 3, 2020, 9:12 AM

  Presenters

  • Satoshi Watanabe

    • The University of Tokyo
    • Department of Materials Engineering, The University of Tokyo

  Authors

  • Satoshi Watanabe

    • The University of Tokyo
    • Department of Materials Engineering, The University of Tokyo

  • Koji Shimizu

    • The University of Tokyo
    • Department of Materials Engineering, The University of Tokyo

  • Wenwen Li

    • AIST
    • National Institute of Advanced Industrial Science and Technology

  • Yasunobu Ando

    • CD-FMat, AIST
    • AIST
    • National Institute of Advanced Industrial Science and Technology

  • Emi Minamitani

    • Institute for Molecular Science

  • Seungwu Han

    • Seoul National University
    • Seoul Natl Univ

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• Embedding physics in machine learning potentials

  Invited

  March 3, 2020, 9:12 AM – March 3, 2020, 9:48 AM

  Presenters

  • Albert Bartok

    • Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick

  Authors

  • Gábor Csányi

    • Department of Engineering, University of Cambridge

  • Albert Bartok

    • Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick

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• Automated training of machine learned potentials with Bayesian active learning

  Invited

  March 3, 2020, 9:48 AM – March 3, 2020, 10:24 AM

  Presenters

  • Jonathan Vandermause

    • Harvard University
    • School of Engineering and Applied Science, Harvard University

  Authors

  • Jonathan Vandermause

    • Harvard University
    • School of Engineering and Applied Science, Harvard University

  • Yu Xie

    • Harvard University
    • School of Engineering and Applied Science, Harvard University

  • Lixin Sun

    • Harvard University
    • School of Engineering and Applied Science, Harvard University

  • Jin Soo S Lim

    • Harvard University

  • Steven B Torrisi

    • Harvard University

  • Simon Batzner

    • Harvard University
    • School of Engineering and Applied Science, Harvard University

  • Alexie Kolpak

    • Massachusetts Institute of Technology

  • Boris Kozinsky

    • Harvard University
    • School of Engineering and Applied Sciences, Harvard University
    • School of Engineering and Applied Science, Harvard University

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• Machine-learning interatomic potentials: a story about how a Big Data approach compensates for our incomplete understanding of interatomic interaction

  Invited

  March 3, 2020, 10:24 AM – March 3, 2020, 11:00 AM

  Presenters

  • Alexander Shapeev

    • Skolkovo Institute of Science and Technology

  Authors

  • Alexander Shapeev

    • Skolkovo Institute of Science and Technology

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