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AI and Statistical/Thermal Physics

FOCUS · B60 · ID: 381720

Presentations

  • Learning about learning by many-body systems

    Invited

    –

    Presenters

    • Nicole Yunger Halpern

      Harvard Smithsonian Institute, Harvard-Smithsonian ITAMP, Physics, Massachusetts Institute of Technology, Institute for Theoretical Atomic, Molecular, and Optical Physics, Harvard-Smithsonian Center for Astrophysics

    Authors

    • Nicole Yunger Halpern

      Harvard Smithsonian Institute, Harvard-Smithsonian ITAMP, Physics, Massachusetts Institute of Technology, Institute for Theoretical Atomic, Molecular, and Optical Physics, Harvard-Smithsonian Center for Astrophysics

    View abstract →

  • Optimal machine intelligence near the edge of chaos

    ORAL

    –

    Presenters

    • Ling Feng

      Institute of High Performance Computing, A*STAR, Institute of High Performance Computing, A*STAR Singapore

    Authors

    • Ling Feng

      Institute of High Performance Computing, A*STAR, Institute of High Performance Computing, A*STAR Singapore

    • Lin Zhang

      Physics, National University of Singapore

    • Choy Heng Lai

      Department of Physics, National University of Singapore, Physics, National University of Singapore

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  • Asymptotic stability of the neural network and its generalization power

    ORAL

    –

    Presenters

    • Lin Zhang

      Department of Physics, National University of Singapore

    Authors

    • Lin Zhang

      Department of Physics, National University of Singapore

    • Ling Feng

      Institute of High Performance Computing, A*STAR, Institute of High Performance Computing, A*STAR Singapore

    • Kan Chen

      Risk Management Institute, National University of Singapore

    • Choy Heng Lai

      Department of Physics, National University of Singapore, Physics, National University of Singapore

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  • Renormalized Mutual Information for Artificial Scientific Discovery

    ORAL

    –

    Presenters

    • Leopoldo Sarra

      Max Planck Inst for Sci Light

    Authors

    • Leopoldo Sarra

      Max Planck Inst for Sci Light

    • Andrea Aiello

      Marquardt Division, Max Planck Institute for the Science of Light, Max Planck Inst for Sci Light

    • Florian Marquardt

      Univ Erlangen Nuremberg, Max Planck Inst for Sci Light, Max Planck Institute for the Science of Light

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  • How neural nets compress invariant manifolds

    ORAL

    –

    Presenters

    • Leonardo Petrini

      Ecole Polytechnique Federale de Lausanne

    Authors

    • Jonas Paccolat

      Ecole Polytechnique Federale de Lausanne

    • Leonardo Petrini

      Ecole Polytechnique Federale de Lausanne

    • Mario Geiger

      École polytechnique fédérale de Lausanne, Ecole Polytechnique Federale de Lausanne

    • Kevin Tyloo

      Ecole Polytechnique Federale de Lausanne

    • Matthieu Wyart

      Physics of Complex Systems Laboratory, Institute of Physics, École Polytechnique Fédérale de Lausanne, Institute of Physics, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne, Switzerland, EPFL, Ecole Polytechnique Federale de Lausanne

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  • Perturbation Theory for the Information Bottleneck

    ORAL

    –

    Presenters

    • Vudtiwat Ngampruetikorn

      The Graduate Center, City University of New York

    Authors

    • Vudtiwat Ngampruetikorn

      The Graduate Center, City University of New York

    • David J. Schwab

      City University of New York Graduate Center, The Graduate Center, City University of New York

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  • Real-space mutual information neural estimation algorithm for single-step extraction of renormalisation group-relevant degrees of freedom

    ORAL

    –

    Presenters

    • Maciej Koch-Janusz

      Department of Physics, University of Zurich

    Authors

    • Doruk Efe Gokmen

      Institute for Theoretical Physics, ETH Zurich

    • Zohar Ringel

      Hebrew University of Jerusalem, Racah Institute of Physics, The Hebrew University of Jerusalem

    • Sebastian Huber

      Department of Physics, ETH Zurich, Institute for Theoretical Physics, ETH Zurich, ETH Zurich, Physics, ETH Zurich

    • Maciej Koch-Janusz

      Department of Physics, University of Zurich

    View abstract →