Machine Learning Material and Experimental Data II

Presentations

• Identifying quantum phase transitions using artificial neural networks on experimental data

  Invited

  March 4, 2019, 11:15 AM – March 4, 2019, 11:51 AM

  Presenters

  • Christof Weitenberg

    • University of Hamburg

  Authors

  • Christof Weitenberg

    • University of Hamburg

  View abstract →

• Classifying Snapshots of the Doped Hubbard Model with Machine Learning

  ORAL

  March 4, 2019, 11:51 AM – March 4, 2019, 12:03 PM

  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 →

• Detecting nematic order in STM/STS data with artificial intelligence

  ORAL

  March 4, 2019, 12:03 PM – March 4, 2019, 12:15 PM

  Presenters

  • Jeremy Goetz

    • Binghamton University

  Authors

  • Jeremy Goetz

    • Binghamton University

  • Yi Zhang

    • Cornell University
    • Department of Physics, Cornell University

  • Michael Lawler

    • Department of Physics, Cornell University, USA
    • Department of Physics, Cornell University

  View abstract →

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

  ORAL

  March 4, 2019, 12:15 PM – March 4, 2019, 12:27 PM

  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

  View abstract →

• Crystal Structure Prediction by Bayesian Optimization and Evolutionary Algorithm

  ORAL

  March 4, 2019, 12:27 PM – March 4, 2019, 12:39 PM

  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

  View abstract →

• Phonon Calculations of Phase Change Materials Using Machine-Learning Methods

  ORAL

  March 4, 2019, 12:39 PM – March 4, 2019, 12:51 PM

  Presenters

  • Youngjae Choi

    • POSTECH, Korean Physical Society

  Authors

  • Youngjae Choi

    • POSTECH, Korean Physical Society

  • Wooil Yang

    • POSTECH, Korean Physical Society

  • Seung-Hoon Jhi

    • POSTECH, Korean Physical Society

  View abstract →

• Developing computationally efficient potential models by genetic programming

  ORAL

  March 4, 2019, 12:51 PM – March 4, 2019, 1:03 PM

  Presenters

  • Alberto Hernandez

    • Johns Hopkins University

  Authors

  • Alberto Hernandez

    • Johns Hopkins University

  • Adarsh Balasubramanian

    • Johns Hopkins University

  • Fenglin Yuan

    • Johns Hopkins University

  • Tim Mueller

    • Materials Science and Engineering, Johns Hopkins University
    • Johns Hopkins University

  View abstract →

• ICA method for identifying collective modes

  ORAL

  March 4, 2019, 1:03 PM – March 4, 2019, 1:15 PM

  Presenters

  • Yadong Wu

    • Tsinghua University

  Authors

  • Yadong Wu

    • Tsinghua University

  • Hui Zhai

    • Tsinghua University

  View abstract →

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

  ORAL

  March 4, 2019, 1:15 PM – March 4, 2019, 1:27 PM

  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

  View abstract →

• Deep Learning of Lennard-Jones Potential Parameterization

  ORAL

  March 4, 2019, 1:27 PM – March 4, 2019, 1:39 PM

  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

  View abstract →

• A direct and local deep learning model for atomic forces in solids

  ORAL

  March 4, 2019, 1:39 PM – March 4, 2019, 1:51 PM

  Presenters

  • Amir Natan

    • Physical Electronics, Tel-Aviv University

  Authors

  • Natalia Kuritz

    • Physical Electronics, Tel-Aviv University

  • Goren Gordon

    • Industrial Engineering, Tel-Aviv University

  • Amir Natan

    • Physical Electronics, Tel-Aviv University

  View abstract →

• Machine Learning Correlates CDW Properties with Local Gap in Cuprates

  ORAL

  March 4, 2019, 1:51 PM – March 4, 2019, 2:03 PM

  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

  View abstract →