Machine Learning Meets Statistical Physics II
FOCUS · MAR-L69 · ID: 3096900
Presentations
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Variational gradient descent: enhancing generalization with automatically learned landscape-dependent noise.
ORAL · Invited
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Presenters
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David Hathcock
IBM Thomas J. Watson Research Center
Authors
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David Hathcock
IBM Thomas J. Watson Research Center
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Yuhai Tu
IBM Thomas J. Watson Research Center
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Top-Down approach to dynamical coarse-graining using Differentiable Generalized Langevin Equation
ORAL
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Publication: Jeong, Jinu, Ishan Nadkarni, and Narayana Aluru. "DiffGLE: Differentiable Coarse-Grained Dynamics using Generalized Langevin Equation." arXiv preprint arXiv:2410.08424 (2024).
Presenters
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Ishan Mangesh Nadkarni
The University of Texas at Austin
Authors
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Ishan Mangesh Nadkarni
The University of Texas at Austin
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Jinu Jeong
University of Illinois at Urbana−Champaign, Urbana, The University of Illinois at Urbana-Champaign
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Narayana R Aluru
The University of Texas at Austin, University of Texas at Austin
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The Manifold Packing Loss Function: A Physics-Inspired Approach to Contrastive Self-Supervised Learning
ORAL
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Presenters
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Guanming Zhang
New York University (NYU)
Authors
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Guanming Zhang
New York University (NYU)
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David J Heeger
New York University
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Stefano Martiniani
New York University (NYU)
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Mutual Information Can Be Estimated when Undersampled Data Have Low-Dimensional Latent Structure
ORAL
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Presenters
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Eslam Abdelaleem
Georgia Institute of Technology
Authors
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Eslam Abdelaleem
Georgia Institute of Technology
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K. Michael Martini
Emory University
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Ilya M Nemenman
Emory University
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Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
ORAL
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Publication: Tianyu He, Darshil Doshi, Aritra Das, Andrey Gromov; "Learning to grok: Emergence of in-context learning and skill compostion in modular arithmetic tasks"; NeurIPS 2024 (Oral)
Presenters
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Darshil H Doshi
University of Maryland College Park
Authors
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Darshil H Doshi
University of Maryland College Park
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Tianyu He
University of Maryland College Park
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Aritra Das
University of Maryland, College Park, University of Maryland College Park
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Andrey Gromov
University of Maryland College Park
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Specialization-generalization transition in exemplar-based in-context learning
ORAL
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Presenters
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Chase Waring Goddard
Princeton University
Authors
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Chase Waring Goddard
Princeton University
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Lindsay Maleckar Smith
Princeton University
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Vudtiwat Ngampruetikorn
University of Sydney
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David J Schwab
CUNY Graduate Center, The Graduate Center, CUNY, CUNY
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Diffusion Models as an Extension of Variational Autoencoders
ORAL
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Presenters
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Kentaro Kaba
Institute of Science Tokyo
Authors
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Kentaro Kaba
Institute of Science Tokyo
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Reo Shimizu
Tohoku University
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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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Yuki Sughiyama
Tohoku University
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Origins and mitigation of double descent in sparse sensing
ORAL
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Publication: Andrei A. Klishin, Samuel E. Otto, J. Nathan Kutz, Krithika Manohar, in preparation (2024)
Presenters
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Andrei A. Klishin
University of Hawaiʻi at Mānoa
Authors
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Andrei A. Klishin
University of Hawaiʻi at Mānoa
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Samuel E Otto
Cornell University
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J. Nathan Kutz
University of Washington, AI Institute for Dynamic Systems
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Krithika Manohar
University of Washington
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Statistical Mechanics of Double Descent in Deep Learning: a Phase Transition Perspective
ORAL
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Presenters
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Chan Li
University of California, San Diego
Authors
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Chan Li
University of California, San Diego
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Nigel Goldenfeld
University of California, San Diego
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LLMs Learn Physical Rules of Dynamical Systems: A Geometric Investigation of Emergent Algorithms
ORAL
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Publication: T. J.B. Liu, N. Boullé, R. Sarfati, & C. J. Earls, LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law, EMNLP (2024)
Liu, T.J., Boull'e, N., Sarfati, R., & Earls, C.J. Density estimation with LLMs: a geometric investigation of in-context learning trajectories, (2024)Presenters
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Toni Jianbang Liu
Cornell University
Authors
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Toni Jianbang Liu
Cornell University
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Raphael Sarfati
Cornell University
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Christopher Earls
Cornell University, Cornell university
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Nicolas Boulle
Imperial College London
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Physics-Inspired Model Compression of Neural Networks
ORAL
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Presenters
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Daniel T Bernstein
Princeton University
Authors
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Daniel T Bernstein
Princeton University
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David J Schwab
CUNY Graduate Center, The Graduate Center, CUNY, CUNY
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Long-range order in classification tasks
ORAL
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Publication: Zhang, YH., Sipling, C., Qiu, E. et al. Collective dynamics and long-range order in thermal neuristor networks. Nat Commun 15, 6986 (2024). https://doi.org/10.1038/s41467-024-51254-4
Computing with long-range order: when, why, and how. In preparation.Presenters
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Yuan-Hang Zhang
University of California, San Diego
Authors
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Yuan-Hang Zhang
University of California, San Diego
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Chesson Sipling
University of California, San Diego
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Massimiliano Di Ventra
University of California, San Diego
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