Machine Learning in Classical and Quantum Many-body Physics

Presentations

• Modeling Many-Body Physics with Restricted Boltzmann Machines

  Invited

  March 5, 2018, 8:00 AM – March 5, 2018, 8:36 AM

  Presenters

  • Roger Melko

    • Perimeter Institute for Theoretical Physics
    • University of Waterloo
    • Univ of Waterloo

  Authors

  • Roger Melko

    • Perimeter Institute for Theoretical Physics
    • University of Waterloo
    • Univ of Waterloo

  View abstract →

• Neural-network Quantum States

  Invited

  March 5, 2018, 8:36 AM – March 5, 2018, 9:12 AM

  Presenters

  • Giuseppe Carleo

    • Institute for Theoretical Physics, ETH
    • ETH
    • ITP, ETH Zurich

  Authors

  • Giuseppe Carleo

    • Institute for Theoretical Physics, ETH
    • ETH
    • ITP, ETH Zurich

  • Matthias Troyer

    • Microsoft Research
    • Quantum Architectures and Computation Group, Microsoft Research
    • Microsoft
    • ITP, ETH Zurich

  • Giacomo Torlai

    • University of Waterloo

  • Roger Melko

    • Perimeter Institute for Theoretical Physics
    • University of Waterloo
    • Univ of Waterloo

  • Juan Carrasquilla

    • Dwave
    • D-Wave INC

  • Guglielmo Mazzola

    • ETH
    • ITP, ETH Zurich

  View abstract →

• Machine learning and the magnetic phases of correlated fermions

  COFFEE_KLATCH · Invited

  March 5, 2018, 9:12 AM – March 5, 2018, 9:48 AM

  Presenters

  • Ehsan Khatami

    • San Jose State Univ
    • San Jose State University
    • Physics and Astronomy, San Jose State University

  Authors

  • Ehsan Khatami

    • San Jose State Univ
    • San Jose State University
    • Physics and Astronomy, San Jose State University

  • Kelvin Ch'ng

    • San Jose State University

  • Nick Vasquez

    • San Jose State University

  • Juan Carrasquilla

    • D-Wave

  • Roger G. Melko

    • Perimeter Institute, University of Waterloo

  View abstract →

• Machine learning of quantum many-fermion systems

  Invited

  March 5, 2018, 9:48 AM – March 5, 2018, 10:24 AM

  Presenters

  • Simon Trebst

    • Univ Cologne
    • University of Cologne
    • Institute for Theoretical Physics, University of Cologne

  Authors

  • Simon Trebst

    • Univ Cologne
    • University of Cologne
    • Institute for Theoretical Physics, University of Cologne

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• Self-Learning Monte Carlo Methods

  Invited

  March 5, 2018, 10:24 AM – March 5, 2018, 11:00 AM

  Presenters

  • Yang Qi

    • Department of Physics, Massachusetts Institute of Technology
    • Department of physics, Massachusetts Institute of Technology

  Authors

  • Yang Qi

    • Department of Physics, Massachusetts Institute of Technology
    • Department of physics, Massachusetts Institute of Technology

  View abstract →