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Statistical Physics Meets Machine Learning

INVITED · B12 · ID: 781082

Presentations

  • Modern Hopfield Networks in AI and Neurobiology

    ORAL · Invited

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    Publication: 1. Krotov, D. and Hopfield, J.J., 2016. Dense associative memory for pattern recognition. Advances in neural information processing systems, 29.<br>2. Krotov, D. and Hopfield, J.J., 2020, September. Large Associative Memory Problem in Neurobiology and Machine Learning. In International Conference on Learning Representations.<br>3. Krotov, D., 2021. Hierarchical associative memory. arXiv preprint arXiv:2107.06446.

    Presenters

    • Dmitry Krotov

      IBM Research

    Authors

    • Dmitry Krotov

      IBM Research

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  • A Picture of the Prediction Space of Deep Networks

    ORAL · Invited

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    Publication: 1. Yang, R., Mao, J. & Chaudhari, P. Does the Data Induce Capacity Control in Deep Learning? Proc. of the International Conference of Machine Learning (2022). arXiv: https://arxiv.org/abs/2110.14163<br>2. Mao, J., Griniasty, I., Yang, R., Teoh, H. K., Ramesh, R., Transtrum, M., Sethna, J. & Chaudhari, P. A Picture of<br>the Prediction Space of Deep Neural Networks (in preparation).<br>3. Ramesh, R., Mao, J., Griniasty, I., Yang, R., Teoh, H. K., Transtrum, M., Sethna, J. & Chaudhari, P. A Picture of<br>the Space of Learning Tasks (in preparation).

    Presenters

    • Pratik Chaudhari

      University of Pennsylvania

    Authors

    • Jialin Mao

      University of Pennsylvania

    • Itay Griniasty

      Cornell University

    • Rubing Yang

      University of Pennsylvania

    • Han Kheng Teoh

      Cornell University

    • Rahul Ramesh

      University of Pennsylvania

    • Mark K Transtrum

      Brigham Young University

    • James P Sethna

      Cornell University

    • Pratik Chaudhari

      University of Pennsylvania

    View abstract →