Machine Learning in Condensed Matter Physics II

Presentations

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

  ORAL · Invited

  March 6, 2018, 11:15 AM – March 6, 2018, 11:51 AM

  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

  View abstract →

• Machine learning out-of-equilibrium phases of matter

  ORAL

  March 6, 2018, 11:51 AM – March 6, 2018, 12:03 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, 12:03 PM – March 6, 2018, 12:15 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, 12:15 PM – March 6, 2018, 12:27 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, 12:27 PM – March 6, 2018, 12:39 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, 12:39 PM – March 6, 2018, 12:51 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, 12:51 PM – March 6, 2018, 1:03 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, 1:03 PM – March 6, 2018, 1:15 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, 1:15 PM – March 6, 2018, 1:27 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, 1:27 PM – March 6, 2018, 1:39 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, 1:39 PM – March 6, 2018, 1:51 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, 1:51 PM – March 6, 2018, 2:03 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, 2:03 PM – March 6, 2018, 2:15 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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