Machine Learning for Quantum Matter II

Presentations

• Materials discovery through artificial intelligence

  Invited

  March 4, 2020, 11:15 AM – March 4, 2020, 11:51 AM

  Presenters

  • Muratahan Aykol

    • Toyota Research Institute

  Authors

  • Muratahan Aykol

    • Toyota Research Institute

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• Working without data: overcoming gaps in deep learning and physics-based extrapolation

  Invited

  March 4, 2020, 11:51 AM – March 4, 2020, 12:27 PM

  Presenters

  • Isaac Tamblyn

    • Natl Res Council
    • National Research Council of Canada

  Authors

  • Isaac Tamblyn

    • Natl Res Council
    • National Research Council of Canada

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• Machine learning models of properties of hybrid 2D materials as potential super lubricants

  ORAL

  March 4, 2020, 12:27 PM – March 4, 2020, 12:39 PM

  Presenters

  • Marco Fronzi

    • IRCRE, Xi'an Jiaotong University

  Authors

  • Marco Fronzi

    • IRCRE, Xi'an Jiaotong University

  • Mutaz Abu Ghazaleh

    • University of Technology Sydney

  • Olexandr Isayev

    • University of North Carolina

  • David Winkler

    • La Trobe University

  • joe shapter

    • Flinders University

  • Michael J Ford

    • University of Technology Sydney

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• Charge Density Prediction through 3D-CNN for Fast Convergence of Self-Consistent DFT calculation

  ORAL

  March 4, 2020, 12:39 PM – March 4, 2020, 12:51 PM

  Presenters

  • Iori Kurata

    • Univ of Tokyo

  Authors

  • Iori Kurata

    • Univ of Tokyo

  • Chikashi Shinagawa

    • Preferred Networks, Inc.

  • Ryohto Sawada

    • Preferred Networks, Inc.

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• Data-driven studies of the magnetic anisotropy of two-dimensional magnetic materials

  ORAL

  March 4, 2020, 12:51 PM – March 4, 2020, 1:03 PM

  Presenters

  • Yiqi Xie

    • Harvard University

  Authors

  • Yiqi Xie

    • Harvard University

  • Trevor David Rhone

    • Harvard University
    • Physics, Rensselaer Polytechnic Institute

  • Georgios Tritsaris

    • Harvard University

  • Oscar Grånäs

    • Uppsala University

  • Efthimios Kaxiras

    • Harvard University
    • Department of Physics, Harvard University

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• Robust cluster expansion of multicomponent systems using machine learning with structured sparsity

  ORAL

  March 4, 2020, 1:03 PM – March 4, 2020, 1:15 PM

  Presenters

  • Zhidong Leong

    • Institute of High Performance Computing

  Authors

  • Zhidong Leong

    • Institute of High Performance Computing

  • Teck Leong Tan

    • Institute of High Performance Computing

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• Generalizing an Energy Predictor based on Wavelet Scattering for 3D Atomic Systems

  ORAL

  March 4, 2020, 1:15 PM – March 4, 2020, 1:27 PM

  Presenters

  • Michael Swift

    • Michigan State Univ

  Authors

  • Paul Sinz

    • Michigan State Univ

  • Michael Swift

    • Michigan State Univ

  • Xavier Brumwell

    • Michigan State Univ

  • Kwang Jin Kim

    • Michigan State Univ

  • Yue Qi

    • Michigan State Univ

  • Matthew J Hirn

    • Michigan State Univ

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• Using Machine Learning Models to Predict Higher-Level Quantities from Energy Models

  ORAL

  March 4, 2020, 1:27 PM – March 4, 2020, 1:39 PM

  Presenters

  • Olivier Malenfant-Thuot

    • Universite de Montreal

  Authors

  • Olivier Malenfant-Thuot

    • Universite de Montreal

  • Michel Cote

    • Universite de Montreal
    • Département de physique, Université de Montréal and RQMP, Montréal, Québec, Canada

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• AI-guided engineering of nanoscale topological materials

  ORAL

  March 4, 2020, 1:39 PM – March 4, 2020, 1:51 PM

  Presenters

  • Srilok Srinivasan

    • Argonne Natl Lab

  Authors

  • Srilok Srinivasan

    • Argonne Natl Lab

  • Mathew J Cherukara

    • Argonne Natl Lab

  • David Jason Eckstein

    • Argonne Natl Lab

  • Anthony Avarca

    • Argonne Natl Lab

  • Subramanian Sankaranarayanan

    • Argonne Natl Lab

  • Pierre Darancet

    • Center for Nanoscale Materials, Argonne National Laboratory
    • Argonne National Lab
    • Argonne Natl Lab

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• Motif-based machine learning for crystalline materials

  ORAL

  March 4, 2020, 1:51 PM – March 4, 2020, 2:03 PM

  Presenters

  • Huta Banjade

    • Physics, Temple University

  Authors

  • Huta Banjade

    • Physics, Temple University

  • Shanshan Zhang

    • Computer and information Sciences, Temple University

  • Sandro Hauri

    • Computer and information Sciences, Temple University

  • Slobodan Vucetic

    • Computer and information Sciences, Temple University

  • Qimin Yan

    • Physics, Temple University
    • Temple Univ

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• Machine learning powered kinetic energy functional finding in solid state physics

  ORAL

  Presenters

  • Hongbin Ren

    • Chinese Academy of Sciences,Institute of Physics

  Authors

  • Hongbin Ren

    • Chinese Academy of Sciences,Institute of Physics

  • Xi Dai

    • Physics, Hong Kong University of Science and Technology
    • Physics Department, Hong Kong University of Science and Technology
    • Physics, Hong Kong University of Science of Technology
    • Hong Kong University of Science and Technology
    • Physics, The Hong Kong University of Science and Technology

  • 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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