Machine Learning for Quantum Matter VI

Presentations

• Differentiable programming tensor networks and quantum circuits

  Invited

  March 6, 2020, 8:00 AM – March 6, 2020, 8:36 AM

  Presenters

  • JinGuo Liu

    • Institute of Physics

  Authors

  • JinGuo Liu

    • Institute of Physics

  • Lei Wang

    • Institute of Physics
    • Institute of Physics, The Chinese Academy of Sciences
    • Chinese Academy of Sciences,Institute of Physics
    • Institute of Physics, Chinese Academy of Sciences

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• Machine learning effective models from a Boltzmann perspective

  ORAL

  March 6, 2020, 8:36 AM – March 6, 2020, 8:48 AM

  Presenters

  • Jonas Rigo

    • Univ Coll Dublin

  Authors

  • Jonas Rigo

    • Univ Coll Dublin

  • Andrew Mitchell

    • Univ Coll Dublin
    • Physics, University College Dublin
    • School of Physics, University College Dublin

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• Automatic design of Hamiltonians

  ORAL

  March 6, 2020, 8:48 AM – March 6, 2020, 9:00 AM

  Presenters

  • Kiryl Pakrouski

    • Princeton University

  Authors

  • Kiryl Pakrouski

    • Princeton University

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• Direct and Reverse Structure-Electronic Property Relationship Prediction with Deep Learning and Bayesian Optimization

  ORAL

  March 6, 2020, 9:00 AM – March 6, 2020, 9:12 AM

  Presenters

  • Artem Pimachev

    • Aerospace Engineering, University of Colorado at Boulder
    • Univ of Wyoming

  Authors

  • Artem Pimachev

    • Aerospace Engineering, University of Colorado at Boulder
    • Univ of Wyoming

  • Sanghamitra Neogi

    • Aerospace Engineering, University of Colorado at Boulder
    • University of Colorado, Boulder
    • Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado, Boulder

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• Machine Learning of Single-Atom Defects in 2D Transition Metal Dichalcogenides with Sub-Picometer Precision

  ORAL

  March 6, 2020, 9:12 AM – March 6, 2020, 9:24 AM

  Presenters

  • Abid Khan

    • University of Illinois at Urbana-Champaign

  Authors

  • Abid Khan

    • University of Illinois at Urbana-Champaign

  • Bryan Clark

    • University of Illinois at Urbana-Champaign

  • Chia-Hao Lee

    • University of Illinois at Urbana-Champaign

  • Di Luo

    • University of Illinois at Urbana-Champaign

  • Chuqiao Shi

    • University of Illinois at Urbana-Champaign

  • Sangmin Kang

    • University of Illinois at Urbana-Champaign

  • Wenjuan Zhu

    • University of Illinois at Urbana-Champaign

  • Pinshane Huang

    • University of Illinois at Urbana-Champaign

  View abstract →

• Dictionary Learning in Fourier Transform Scanning Tunneling Spectroscopy

  ORAL

  March 6, 2020, 9:24 AM – March 6, 2020, 9:36 AM

  Presenters

  • Yenson Lau

    • Columbia Univ

  Authors

  • Jedrzej Wieteska

    • Columbia Univ
    • Physics, Columbia University

  • Yenson Lau

    • Columbia Univ

  • Tetsuo Hanaguri

    • Center for Emergent Matter Science, RIKEN
    • RIKEN
    • CEMS, RIKEN
    • RIKEN CEMS

  • John Wright

    • Columbia Univ

  • Ilya Eremin

    • Institute for Theoretical Physics, Ruhr-Universität Bochum
    • Ruhr Univ Bochum

  • Abhay Pasupathy

    • Columbia University
    • Physics Department, Columbia University
    • Columbia Univ
    • Department of Physics, Columbia University, New York, New York 10027, USA
    • Physics, Columbia University
    • Department of Physics, Columbia University

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• Machine Learning Tool for Crystal Structure Predictions

  ORAL

  March 6, 2020, 9:36 AM – March 6, 2020, 9:48 AM

  Presenters

  • Valentin Stanev

    • University of Maryland, College Park

  Authors

  • Valentin Stanev

    • University of Maryland, College Park

  • Haotong Liang

    • University of Maryland, College Park

  • Aaron Kusne

    • National Institute of Standards and Technology, Gaithersburg, MD

  • Ichiro Takeuchi

    • University of Maryland, College Park

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• Transferable and interpretable machine learning model for four-dimensional scanning transmission electron microscopy data

  ORAL

  March 6, 2020, 9:48 AM – March 6, 2020, 10:00 AM

  Presenters

  • Michael Matty

    • Physics, Cornell University
    • Cornell University

  Authors

  • Michael Matty

    • Physics, Cornell University
    • Cornell University

  • Michael Cao

    • Cornell University
    • Applied and Engineering Physics, Cornell University

  • Zhen Chen

    • Applied and Engineering Physics, Cornell University
    • Cornell University
    • School of Applied and Engineering Physics, Cornell University

  • Li Li

    • Google Research

  • David Muller

    • Cornell University
    • School of Applied and Engineering Physics, Cornell University
    • Applied and Engineering Physics, Cornell University

  View abstract →

• Tight-binding deep learning approach to band structures calculations

  ORAL

  March 6, 2020, 10:00 AM – March 6, 2020, 10:12 AM

  Presenters

  • Florian Sapper

    • Max Planck Inst for Sci Light

  Authors

  • Florian Sapper

    • Max Planck Inst for Sci Light

  • Vittorio Peano

    • Max Planck Inst for Sci Light
    • Max Planck Institute for the Science of Light

  • Florian Marquardt

    • Max Planck Inst for Sci Light
    • Max Planck Institute for the Science of Light

  View abstract →