Machine Learning in Condensed Matter Physics IV

Presentations

• Tensor Network Machine Learning Models

  Invited

  March 8, 2018, 8:00 AM – March 8, 2018, 8:36 AM

  Presenters

  • Edwin Stoudenmire

    • Center for Computational Quantum Physics, Flatiron Institute
    • University of California - Irvine
    • Department of Physics and Astronomy, University of California at Irvine

  Authors

  • Edwin Stoudenmire

    • Center for Computational Quantum Physics, Flatiron Institute
    • University of California - Irvine
    • Department of Physics and Astronomy, University of California at Irvine

  View abstract →

• Unifying Quantum Tensor Network and Convolutional Neural Network

  ORAL

  March 8, 2018, 8:36 AM – March 8, 2018, 8:48 AM

  Presenters

  • Yahui Zhang

    • Physics, Massachusetts Inst of Tech-MIT

  Authors

  • Yahui Zhang

    • Physics, Massachusetts Inst of Tech-MIT

  View abstract →

• Efficient Representation of Matrx Product State with Restricted Boltzmann Machine

  ORAL

  March 8, 2018, 8:48 AM – March 8, 2018, 9:00 AM

  Presenters

  • Zhengyu Zhang

    • Department of Physics, Univ of Michigan - Ann Arbor

  Authors

  • Zhengyu Zhang

    • Department of Physics, Univ of Michigan - Ann Arbor

  • Xun Gao

    • Center for Quantum Information, IIIS, Tsinghua University

  • Luming Duan

    • Department of Physics, University of Michigan
    • Tsinghua Univ
    • Department of Physics, Univ of Michigan - Ann Arbor
    • Tsinghua University
    • IIIS, Center for Quantum Information
    • University of Michigan

  View abstract →

• Machine Learning Spatial Geometry from Entanglement Features

  ORAL

  March 8, 2018, 9:00 AM – March 8, 2018, 9:12 AM

  Presenters

  • Yizhuang You

    • Physics, Harvard University
    • Harvard
    • Harvard University

  Authors

  • Yizhuang You

    • Physics, Harvard University
    • Harvard
    • Harvard University

  • Zhao Yang

    • Stanford University

  • Xiaoliang Qi

    • Stanford University

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• Thermodynamics-inspired unsupervised clustering of objects

  ORAL

  March 8, 2018, 9:12 AM – March 8, 2018, 9:24 AM

  Presenters

  • Jorge Munoz

    • Intel Corporation
    • The Datum Institute

  Authors

  • Jorge Munoz

    • Intel Corporation
    • The Datum Institute

  View abstract →

• Designing Error-Correction Codes by Machine Learning

  ORAL

  March 8, 2018, 9:24 AM – March 8, 2018, 9:36 AM

  Presenters

  • Ye-Hua Liu

    • Institut Quantique, Université de Sherbrooke

  Authors

  • Ye-Hua Liu

    • Institut Quantique, Université de Sherbrooke

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• Morse-Smale Systems and Machine Learning

  ORAL

  March 8, 2018, 9:36 AM – March 8, 2018, 9:48 AM

  Presenters

  • Kyle Kawagoe

    • Physics, University of Chicago

  Authors

  • Kyle Kawagoe

    • Physics, University of Chicago

  • Arvind Murugan

    • Physics, University of Chicago
    • University of Chicago
    • James Franck Institute, University of Chicago

  View abstract →

• Self-learning Monte Carlo Method with Deep Neural Networks

  ORAL

  March 8, 2018, 9:48 AM – March 8, 2018, 10:00 AM

  Presenters

  • Junwei Liu

    • Massachusetts Inst of Tech-MIT
    • Physics, Hong Kong University of Science and Technology
    • Physics, MIT

  Authors

  • Junwei Liu

    • Massachusetts Inst of Tech-MIT
    • Physics, Hong Kong University of Science and Technology
    • Physics, MIT

  • Huitao Shen

    • Physics, Massachusetts Inst of Technology
    • Massachusetts Institute of Technology

  • Liang Fu

    • Department of Physics, Massachusetts Institute of Technology
    • Massachusetts Inst of Tech-MIT
    • Physics, Massachusetts Inst of Tech-MIT
    • Physics, Massachusetts Institute of Technology
    • Physics, Massachusetts Inst of Technology
    • Physics, MIT
    • Massachusetts Institute of Technology
    • MIT

  View abstract →

• Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines

  ORAL

  March 8, 2018, 10:00 AM – March 8, 2018, 10:12 AM

  Presenters

  • Li Huang

    • China Academy of Engineering Physics

  Authors

  • Li Huang

    • China Academy of Engineering Physics

  • Lei Wang

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

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• Model parameter learning using Kullback-Leibler divergence

  ORAL

  March 8, 2018, 10:12 AM – March 8, 2018, 10:24 AM

  Presenters

  • Chungwei Lin

    • Mitsubishi Electric Research Laboratories

  Authors

  • Chungwei Lin

    • Mitsubishi Electric Research Laboratories

  • Chih-kuan Tung

    • Physics, North Carolina Agricultural and Technical State University

  View abstract →

• SchNet - A Deep Learning Architecture for Molecules and Materials

  ORAL

  March 8, 2018, 10:24 AM – March 8, 2018, 10:36 AM

  Presenters

  • 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

  Authors

  • Kristof Schütt

    • TU Berlin

  • Huziel Sauceda

    • Fritz-Haber-Institut der Max-Planck-Gesellschaft

  • Pieter-Jan Kindermans

    • TU Berlin

  • Stefan Chmiela

    • TU Berlin
    • Technische Universität Berlin

  • 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

  View abstract →

• Deep Potential Molecular Dynamics: a Scalable Model with the Accuracy of Quantum Mechanics

  ORAL

  March 8, 2018, 10:36 AM – March 8, 2018, 10:48 AM

  Presenters

  • Linfeng Zhang

    • Program in Applied and Computational Mathmatics, Princeton University

  Authors

  • Linfeng Zhang

    • Program in Applied and Computational Mathmatics, Princeton University

  • Jiequn Han

    • Program in Applied and Computational Mathmatics, Princeton University

  • Han Wang

    • Institute of Applied Physics and Computational Mathematics

  • Roberto Car

    • Department of Chemistry, Princeton
    • Department of Chemistry, Princeton Univ
    • Department of Chemistry , Princeton University
    • Princeton University
    • Physics, Princeton University
    • Department of Chemistry, Princeton University

  • Weinan E

    • Program in Applied and Computational Mathmatics, Princeton University

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• Translating accurate electronic structure calculations into an accurate calculation of dynamical properties in liquid water via the neural network.

  ORAL

  March 8, 2018, 10:48 AM – March 8, 2018, 11:00 AM

  Presenters

  • Yi Yao

    • Chemistry, Univ of NC - Chapel Hill

  Authors

  • Yi Yao

    • Chemistry, Univ of NC - Chapel Hill

  • Yosuke Kanai

    • Chemistry, Univ of NC - Chapel Hill
    • Department of Chemistry, Univ of NC - Chapel Hill

  View abstract →