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Machine Learning Meets Statistical Physics I

FOCUS · MAR-J69 · ID: 3096930

Presentations

  • How do neural networks learn simple functions?

    ORAL · Invited

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    Publication: * How Two-Layer Neural Networks Learn, One (Giant) Step at a Time, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan, to appear in JMLR<br>* The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents, Yatin Dandi, Emanuele Troiani, Luca Arnaboldi, Luca Pesce, Lenka Zdeborová, Florent Krzakala, ICML 2024<br>* Fundamental computational limits of weak learnability in high-dimensional multi-index models<br>Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala, arXiv:2405.15480<br>* Repetita iuvant: Data repetition allows sgd to learn high-dimensional multi-index functions<br>L Arnaboldi, Y Dandi, F Krzakala, L Pesce, L Stephan, preprint arXiv:2405.15459

    Presenters

    • FLORENT KRZAKALA

      EPFL

    Authors

    • FLORENT KRZAKALA

      EPFL

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  • Minimax entropy: The statistical physics of optimal constraints

    ORAL

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    Publication: 1. Christopher W. Lynn, Qiwei Yu, Rich Pang, William Bialek, & Stephanie E. Palmer. Exactly solvable statistical physics models for large neuronal populations. Preprint: arxiv.org/abs/2310.10860.<br>2. Christopher W. Lynn, Qiwei Yu, Rich Pang, William Bialek, & Stephanie E. Palmer. Exact minimax entropy models of large-scale neuronal activity. Preprint: https://arxiv.org/abs/2402.00007.<br>3. David Carcamo and Christopher W. Lynn. Statistical physics of large-scale neural activity with loops. In preparation.

    Presenters

    • Christopher W Lynn

      Yale University

    Authors

    • Christopher W Lynn

      Yale University

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  • Lines of Thought in Large Language Models

    ORAL

    –

    Publication: https://arxiv.org/abs/2410.01545

    Presenters

    • Raphael Sarfati

      Cornell University

    Authors

    • Raphael Sarfati

      Cornell University

    • Toni Jianbang Liu

      Cornell University

    • Nicolas Boulle

      Imperial College London

    • Christopher Earls

      Cornell University, Cornell university

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  • Adaptively Guided Multimodal Conditional Latent Diffusion for Complex Dynamic Systems

    ORAL

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    Publication: Scheinker, Alexander. "cDVAE: Multimodal Generative Conditional Diffusion Guided by Variational Autoencoder Latent Embedding for Virtual 6D Phase Space Diagnostics." arXiv preprint arXiv:2407.20218 (2024).

    Presenters

    • Alexander Scheinker

      Los Alamos National Laboratory (LANL)

    Authors

    • Alexander Scheinker

      Los Alamos National Laboratory (LANL)

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  • Learning of statistical field theories

    ORAL

    –

    Presenters

    • Shreya Shukla

      Los Alamos National Laboratory

    Authors

    • Shreya Shukla

      Los Alamos National Laboratory

    • Abhijith Jayakumar

      Los Alamos National Laboratory (LANL)

    • Andrey Y Lokhov

      Los Alamos National Laboratory (LANL), Los Alamos National Laboratory

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  • Surrogate-assisted Simulated Annealing

    ORAL

    –

    Presenters

    • Yuta Ozaki

      Department of Physics, Institute of Science Tokyo

    Authors

    • Yuta Ozaki

      Department of Physics, Institute of Science Tokyo

    • Masayuki Ohzeki

      Graduate School of Information Sciences, Tohoku University, Department of Physics, Institute of Science Tokyo, Sigma-i Co., Ltd., Institute of Science Tokyo, Tohoku University, Sigma-i Co., Ltd.,, Graduate School of Information Sciences, Tohoku University; Department of Physics, Institute of Science Tokyo; Sigma-i Co., Ltd.

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