Machine Learning in Condensed Matter Physics II

Presentations

• Machine learning a dynamical phase diagram for many-body localization

  ORAL · Invited

  March 6, 2018, 2:15 PM – March 6, 2018, 2:51 PM

  Presenters

  • Evert Van Nieuwenburg

    Physics, California Institute of Technology

  Authors

  • Eyal Bairey

    Physics, Technion

  • Gil Refael

    California Institute of Technology, Caltech, Physics, California Institute of Technology, Physics, Caltech

  • Evert Van Nieuwenburg

    Physics, California Institute of Technology

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• Machine learning out-of-equilibrium phases of matter

  ORAL

  March 6, 2018, 2:51 PM – March 6, 2018, 3:03 PM

  Presenters

  • Jordan Venderley

    Cornell Univ

  Authors

  • Jordan Venderley

    Cornell Univ

  • Vedika Khemani

    Physics, Harvard University, Harvard Univ

  • Eun-Ah Kim

    Cornell University, Cornell Univ, Department of Physics, Cornell University, Physics, Cornell University

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• Finite-Size Effects in Machine Learning the Kosterlitz-Thouless Transition

  ORAL

  March 6, 2018, 3:03 PM – March 6, 2018, 3:15 PM

  Presenters

  • Anna Golubeva

    Perimeter Institute for Theoretical Physics

  Authors

  • Anna Golubeva

    Perimeter Institute for Theoretical Physics

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• Machine Learning Vortices in the XY Model

  ORAL

  March 6, 2018, 3:15 PM – March 6, 2018, 3:27 PM

  Presenters

  • Matthew Beach

    University of Waterloo

  Authors

  • Matthew Beach

    University of Waterloo

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• Machine Learning of Frustrated Classical Spin Models

  ORAL

  March 6, 2018, 3:27 PM – March 6, 2018, 3:39 PM

  Presenters

  • Ce Wang

    Tsinghua Univ

  Authors

  • Ce Wang

    Tsinghua Univ

  • Hui Zhai

    Institute for Advanced Study, Tsinghua University, physics, Tsinghua Univ, Tsinghua Univ

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• Machine Learning the Spin-glass State

  ORAL

  March 6, 2018, 3:39 PM – March 6, 2018, 3:51 PM

  Presenters

  • Humberto Munoz-Bauza

    Physics and Astronomy, University of Southern California

  Authors

  • Humberto Munoz-Bauza

    Physics and Astronomy, University of Southern California

  • Firas Hamze

    D-Wave Systems Inc.

  • Helmut Katzgraber

    Texas A&M Univ, Department of Physics and Astronomy, Texas A&M University, Physics and Astronomy, Texas A&M University

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• Extrapolating the properties of lattice polarons with Machine Learning

  ORAL

  March 6, 2018, 3:51 PM – March 6, 2018, 4:03 PM

  Presenters

  • Rodrigo Alejandro Vargas-Hernández

    Chemistry, University of British Columbia

  Authors

  • Rodrigo Alejandro Vargas-Hernández

    Chemistry, University of British Columbia

  • John Sous

    Physics and Astronomy, University of British Columbia

  • Mona Berciu

    Univ of British Columbia, University of British Columbia, Quantum Matter Institute, Physics and Astronomy, University of British Columbia

  • Roman Krems

    Chemistry, University of British Columbia

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• The dangers of inadvertently poisoned training sets in physics applications

  ORAL

  March 6, 2018, 4:03 PM – March 6, 2018, 4:15 PM

  Presenters

  • Chao Fang

    Physics, Texas A&M Univ

  Authors

  • Chao Fang

    Physics, Texas A&M Univ

  • Helmut Katzgraber

    Physics and Astronomy, Texas A&M Univ, Physics, Texas A&M Univ

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• Identification of phase transtitions in molecular systems using unsupervised machine learning methods

  ORAL

  March 6, 2018, 4:15 PM – March 6, 2018, 4:27 PM

  Presenters

  • Nicholas Walker

    Physics & Astronomy, Louisiana State University

  Authors

  • Nicholas Walker

    Physics & Astronomy, Louisiana State University

  • Ka-Ming Tam

    Louisiana State Univ, Physics & Astronomy, Louisiana State University

  • Mark Jarrell

    Louisiana State Univ, Physics & Astronomy, Louisiana State University

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• Linear Scaling, Quantum-accurate Interatomic Potentials with SNAP; Acessing those Hard-to-reach Places in Classical Molecular Dynamics

  ORAL

  March 6, 2018, 4:27 PM – March 6, 2018, 4:39 PM

  Presenters

  • Mitchell Wood

    Center for Computing Research, Sandia Natl Labs

  Authors

  • Mitchell Wood

    Center for Computing Research, Sandia Natl Labs

  • Aidan Thompson

    Sandia Natl Labs, Center for Computing Research, Sandia Natl Labs

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• Learning Force Fields using Covariant Compositional Networks

  ORAL

  March 6, 2018, 4:39 PM – March 6, 2018, 4:51 PM

  Presenters

  • Brandon Anderson

    Computer Science, University of Chicago

  Authors

  • Brandon Anderson

    Computer Science, University of Chicago

  • Risi Kondor

    Computer Science, University of Chicago

  • Horace Pan

    Computer Science, University of Chicago

  • Shubhendu Trivedi

    Computer Science, University of Chicago

  • Truong Son Hy

    Computer Science, University of Chicago

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• Towards Exact Molecular Dynamics Simulations with Machine-Learned Force Fields

  ORAL

  March 6, 2018, 4:51 PM – March 6, 2018, 5:03 PM

  Presenters

  • Stefan Chmiela

    TU Berlin, Technische Universität Berlin

  Authors

  • Stefan Chmiela

    TU Berlin, Technische Universität Berlin

  • Huziel Sauceda

    Fritz-Haber-Institut der Max-Planck-Gesellschaft

  • Klaus-Robert Müller

    TU Berlin, Technische Universität Berlin

  • Alexandre Tkatchenko

    Université du Luxembourg, University of Luxembourg, Physics and Materials Science Research Unit, University of Luxembourg, Physics and Materials Science Research Unit,, University of Luxembourg

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• Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

  ORAL

  March 6, 2018, 5:03 PM – March 6, 2018, 5:15 PM

  Presenters

  • Tristan Bereau

    Max Planck Institute for Polymer Research

  Authors

  • Tristan Bereau

    Max Planck Institute for Polymer Research

  • Robert Distasio

    Cornell University

  • Alexandre Tkatchenko

    Université du Luxembourg, University of Luxembourg, Physics and Materials Science Research Unit, University of Luxembourg, Physics and Materials Science Research Unit,, University of Luxembourg

  • O. Anatole Von Lilienfeld

    University of Basel

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