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Statistical Physics Meets Machine Learning

ORAL · U24 · ID: 355182

Presentations

  • Reservoir Computer Optimization for Parity Checking

    ORAL

    –

    Presenters

    • Wendson Barbosa

      Department of Physics, The Ohio State University

    Authors

    • Wendson Barbosa

      Department of Physics, The Ohio State University

    • Guilhem Ribeill

      Quantum Engineering and Computation, Raytheon BBN Technologies, BBN Technology - Massachusetts, Raytheon BBN Technologies, BBN Technologies

    • Minh-Hai Nguyen

      Raytheon BBN Technologies

    • Thomas A Ohki

      BBN Technology - Massachusetts, Raytheon BBN Technologies, BBN Technologies

    • Graham E Rowlands

      Raytheon BBN Technologies

    • Daniel J Gauthier

      Department of Physics, The Ohio State University

    View abstract →

  • Using Machine Learning to Infer Composition of Complex Chemical Mixtures

    ORAL

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    Presenters

    • Unab Javed

      Rutgers University, New Brunswick

    Authors

    • Unab Javed

      Rutgers University, New Brunswick

    • Kannan P Ramaiyan

      Los Alamos National Laboratory

    • Cortney R Kreller

      Los Alamos National Laboratory

    • Eric L Brosha

      Los Alamos National Laboratory

    • Rangachary Mukundan

      Los Alamos National Laboratory

    • Alexandre Morozov

      Rutgers University, New Brunswick

    View abstract →

  • Deep generative spin-glass models with normalizing flows

    ORAL

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    Presenters

    • Masoud Mohseni

      Google AI, Google Inc., Google Inc, Google Research, Google Quantum AI Laboratory

    Authors

    • Masoud Mohseni

      Google AI, Google Inc., Google Inc, Google Research, Google Quantum AI Laboratory

    • Gavin Hartnett

      Engineering and Applied Sciences, RAND Corporation, Rand Cooperation

    View abstract →

  • A Continuous Formulation of Discrete Spin-Glass Systems

    ORAL

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    Presenters

    • Gavin Hartnett

      Engineering and Applied Sciences, RAND Corporation, Rand Cooperation

    Authors

    • Gavin Hartnett

      Engineering and Applied Sciences, RAND Corporation, Rand Cooperation

    • Masoud Mohseni

      Google AI, Google Inc., Google Inc, Google Research, Google Quantum AI Laboratory

    View abstract →

  • Dynamical loss functions for Machine Learning

    ORAL

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    Presenters

    • Miguel Ruiz Garcia

      Univ of Pennsylvania, University of Pennsylvania

    Authors

    • Miguel Ruiz Garcia

      Univ of Pennsylvania, University of Pennsylvania

    • Ge Zhang

      Univ of Pennsylvania, University of Pennsylvania

    • Samuel Schoenholz

      Google Brain, Google

    • Andrea Jo-Wei Liu

      Univ of Pennsylvania, University of Pennsylvania, Department of Physics and Astronomy, University of Pennsylvania, Physics, University of Pennsylvania, Physics and Astronomy, University of Pennsylvania

    View abstract →

  • A mechanical model for supervised learning

    ORAL

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    Presenters

    • Menachem Stern

      University of Chicago

    Authors

    • Menachem Stern

      University of Chicago

    • Chukwunonso Arinze

      University of Chicago

    • Leron Perez

      University of Chicago

    • Stephanie Palmer

      University of Chicago

    • Arvind Murugan

      Physics, University of Chicago, University of Chicago, Department of Physics, University of Chicago

    View abstract →

  • Quantifying statistical mechanical learning in a many-body system with machine learning

    ORAL

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    Presenters

    • Weishun Zhong

      Massachusetts Institute of Technology

    Authors

    • Weishun Zhong

      Massachusetts Institute of Technology

    • Jacob M Gold

      Massachusetts Institute of Technology

    • Sarah Marzen

      Massachusetts Institute of Technology and the Claremont Colleges

    • Jeremy L England

      Massachusetts Institute of Technology and GlaxoSmithKline

    • Nicole Yunger Halpern

      Harvard University and Massachusetts Institute of Technology, Harvard University

    View abstract →

  • Information-bottleneck renormalization group for self-supervised representation learning

    ORAL

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    Presenters

    • Vudtiwat Ngampruetikorn

      Initiative for the Theoretical Sciences, The Graduate Center, City University of New York

    Authors

    • Vudtiwat Ngampruetikorn

      Initiative for the Theoretical Sciences, The Graduate Center, City University of New York

    • William S Bialek

      princeton university, Department of Physics, Princeton University, Princeton University, Physics, Princeton University

    • David J. Schwab

      Institute for Theoretical Science, CUNY Graduate Center, Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, City University of New York

    View abstract →

  • Deep Learning on the 2-Dimensional Ising Model to Extract the Crossover Region

    ORAL

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    Presenters

    • Nicholas Walker

      Louisiana State University, Baton Rouge

    Authors

    • Nicholas Walker

      Louisiana State University, Baton Rouge

    • Ka-Ming Tam

      Physics and Astronomy, Louisiana State University, Louisiana State University, Baton Rouge, Department of Physics, Louisiana State University

    • Mark Jarrell

      Louisiana State University, Baton Rouge, Louisiana State University, Baton Rouge, Louisiana 70803, Department of Physics, Louisiana State University

    View abstract →

  • Training and classification using Restricted Boltzmann Machine (RBM) on the D-Wave 2000Q

    ORAL

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    Presenters

    • Vivek Dixit

      Purdue Univ

    Authors

    • Vivek Dixit

      Purdue Univ

    • Sabre Kais

      Department of Chemistry, Department of Physics and Astronomy, and Birck Nanotechnology Center, Purdue University, Purdue Univ, Department of Chemistry and Physics, Purdue Univ, Department of Physics, Department of Chemistry, and the Birck Nanotechnology Center, Purdue Univ

    • Muhammad A Alam

      Purdue Univ

    View abstract →