Learning in Physical Systems

Presentations

• How a time-reversal-invariant physical system can be turned into a self-learning machine

  ORAL · Invited

  March 15, 2022, 12:30 PM – March 15, 2022, 1:06 PM

  Publication: Self-learning Machines based on Hamiltonian Echo Backpropagation, Victor Lopez-Pastor, Florian Marquardt, arXiv 2103.04992 (2021)

  Presenters

  • Florian Marquardt

    Max Planck Inst for Sci Light, Friedrich-Alexander University Erlangen-Nürnberg, Friedrich-Alexander University Erlangen-Nürnberg, Max Planck Institute for the Science of Light, Friedrich-Alexander University Erlangen-

  Authors

  • Florian Marquardt

    Max Planck Inst for Sci Light, Friedrich-Alexander University Erlangen-Nürnberg, Friedrich-Alexander University Erlangen-Nürnberg, Max Planck Institute for the Science of Light, Friedrich-Alexander University Erlangen-

  • Victor Lopez-Pastor

    Max Planck Institute for the Science of Light

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• Physics for neuromorphic computing

  ORAL · Invited

  March 15, 2022, 1:06 PM – March 15, 2022, 1:42 PM

  Presenters

  • Julie Grollier

    CNRS/Thales

  Authors

  • Julie Grollier

    CNRS/Thales

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• Materials that learn from examples

  ORAL · Invited

  March 15, 2022, 1:42 PM – March 15, 2022, 2:18 PM

  Presenters

  • Arvind Murugan

    University of Chicago

  Authors

  • Arvind Murugan

    University of Chicago

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• Multifunctional networks using local training rules

  ORAL · Invited

  March 15, 2022, 2:18 PM – March 15, 2022, 2:54 PM

  Publication: Local rules for fabricating allosteric networks. Nidhi Pashine. Phys. Rev. Materials 5, 065607<br>Multifunctionality in variable stiffness metamaterials. Nidhi Pashine, Amir M Nasab, Rebecca Kramer-Bottiglio (in preparation)

  Presenters

  • Nidhi Pashine

    Yale University

  Authors

  • Nidhi Pashine

    Yale University

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• Decentralized, Physics-Driven Learning

  ORAL · Invited

  March 15, 2022, 2:54 PM – March 15, 2022, 3:30 PM

  Publication: S Dillavou, M Stern, AJ Liu, DJ Durian. Demonstration of Decentralized Physics-Driven Learning. ArXiv (2021) https://arxiv.org/abs/2108.00275

  Presenters

  • Sam J Dillavou

    University of Pennsylvania

  Authors

  • Sam J Dillavou

    University of Pennsylvania

  • Menachem Stern

    University of Pennsylvania

  • Marc Z Miskin

    University of Pennsylvania

  • Andrea J Liu

    University of Pennsylvania

  • Douglas J Durian

    University of Pennsylvania

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