Machine Learning Material and Experimental Data II

FOCUS · B18

Presentations

  • Classifying Snapshots of the Doped Hubbard Model with Machine Learning

    ORAL

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    Presenters

    • Annabelle Bohrdt

      Physics Department, Technical University of Munich, Harvard University and Technical University of Munich, Harvard University and Technical Unversity of Munich, Physics, TU Munich, Technical University of Munich

    Authors

    • Annabelle Bohrdt

      Physics Department, Technical University of Munich, Harvard University and Technical University of Munich, Harvard University and Technical Unversity of Munich, Physics, TU Munich, Technical University of Munich

    • Christie S Chiu

      Harvard University, Physics Department, Harvard University

    • Geoffrey Ji

      Harvard University, Physics Department, Harvard University

    • Muqing Xu

      Harvard University, Physics Department, Harvard University

    • Daniel Greif

      Harvard University, Physics Department, Harvard University

    • Markus Greiner

      Harvard University, Physics Department, Harvard University

    • Eugene Demler

      Physics Department, Harvard University, Harvard University

    • Fabian Grusdt

      Physics Department, Technical University of Munich, Department of Physics and Institute for Advanced Study, Technical University of Munich, 85748 Garching, Harvard University, Technical University of Munich

    • Michael Knap

      Physics Department, Technical University of Munich, Technical University of Munich, Department of Physics, Technical University of Munich

    View abstract →

  • Revealing Patterns in Scanning Probe Microscopy Data via Machine Learning Techniques

    ORAL

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    Presenters

    • Eric Hudson

      Pennsylvania State University, Department of Physics, Pennsylvania State University

    Authors

    • Eric Hudson

      Pennsylvania State University, Department of Physics, Pennsylvania State University

    • Riju Banerjee

      Pennsylvania State University

    • Lavish Pabbi

      Pennsylvania State University

    • Anna Binion

      Pennsylvania State University

    • Kevin Crust

      Pennsylvania State University

    • William Dusch

      Pennsylvania State University

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  • Crystal Structure Prediction by Bayesian Optimization and Evolutionary Algorithm

    ORAL

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    Presenters

    • Tomoki Yamashita

      National Institute for Materials Science

    Authors

    • Tomoki Yamashita

      National Institute for Materials Science

    • Shinichi Kanehira

      Osaka University

    • Nobuya Sato

      National Institute of Advanced Industrial Science and Technology

    • Hiori Kino

      National Institute for Materials Science

    • Koji Tsuda

      The University of Tokyo

    • Takashi Miyake

      National Institute of Advanced Industrial Science and Technology

    • Tamio Oguchi

      Institute of Scientific and Industrial Research, Osaka University, MaDIS-CMI2, National Institute for Materials Research, Japan, Institute of Scientific and Industrial Research, Institute of Scientific and Industrial Research, Osaka university, Osaka University, The Institute of Scientific and Industrial Research, Osaka University

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  • "Perfect crime" of machine-learning potentials: 100-fold speed-up with no detectable trace of using machine learning in the final result

    ORAL

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    Presenters

    • Alexander Shapeev

      Skolkovo Institute of Science and Technology

    Authors

    • Konstantin Gubaev

      Skolkovo Institute of Science and Technology

    • Evgeny Podryabinkin

      Skolkovo Institute of Science and Technology

    • Gus Hart

      Brigham Young University, Physics and Astronomy, Brigham Young University

    • Alexander Shapeev

      Skolkovo Institute of Science and Technology

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  • Deep Learning of Lennard-Jones Potential Parameterization

    ORAL

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    Presenters

    • Alireza Moradzadeh

      Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, IL, USA

    Authors

    • Alireza Moradzadeh

      Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, IL, USA

    • N. R. Aluru

      Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, IL, USA

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  • Machine Learning Correlates CDW Properties with Local Gap in Cuprates

    ORAL

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    Presenters

    • Kaylie Hausknecht

      Department of Physics, Harvard University

    Authors

    • Kaylie Hausknecht

      Department of Physics, Harvard University

    • Tatiana Webb

      Physics, Harvard University, Department of Physics, Harvard University, Harvard University

    • Michael C Boyer

      Department of Physics, Clark University, Clark University, Physics, Clark University

    • Yi Yin

      Department of Physics, Zhejiang University, Zhejiang University

    • Takeshi Kondo

      ISSP, University of Tokyo, Institute for Solid State Physics, University of Tokyo, University of Tokyo

    • Tsunehiro Takeuchi

      Toyota Technological Institute, Nagoya University

    • Hiroshi Ikuta

      Department of Materials Physics, Nagoya University, Nagoya University

    • Eric Hudson

      Pennsylvania State University, Department of Physics, Pennsylvania State University

    • Jennifer Hoffman

      Physics, Harvard University, Department of Physics, Harvard University, Harvard University, Department of Physics, Harvard University, Cambridge, MA, United States

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