Statistical Physics Meets Machine Learning II
ORAL · MAR-M63 · ID: 3995679
Presentations
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Statistical Mechanics of Function Vectors
ORAL
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Presenters
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Ravin Raj
- Princeton University
Authors
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Ravin Raj
- Princeton University
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Gautam Reddy
- Princeton University
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Adaptively Guided Latent Diffusion for Time-Varying Inverse Problems in Particle Accelerators
ORAL
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Publication: A. Scheinker and A. Williams. "Latent diffusion can map beam loss to two-dimensional phase-space projections." Physical Review Accelerators and Beams 28.9 (2025): 094602. https://doi.org/10.1103/rqg9-g3dp
Presenters
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Alexander Scheinker
- Los Alamos National Laboratory (LANL)
Authors
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Alexander Scheinker
- Los Alamos National Laboratory (LANL)
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Universality of LLM mechanisms across scale and diversity
ORAL
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Presenters
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Lindsay Maleckar Smith
- Princeton University
Authors
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Lindsay Maleckar Smith
- Princeton University
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Gautam Reddy
- Princeton University
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David J Schwab
- The Graduate Center, City University of New York
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Conditioning generative models without retraining: How to make a horse into a car
ORAL
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Presenters
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Huan Souza
- Boston University
Authors
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Huan Souza
- Boston University
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Pankaj Mehta
- Boston University
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Machine learning topological defect formation
ORAL
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Publication: arXiv:2508.20347
Presenters
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Fumika Suzuki
- University of Tokyo ICEPP
- Los Alamos National Laboratory (LANL)
Authors
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Fumika Suzuki
- University of Tokyo ICEPP
- Los Alamos National Laboratory (LANL)
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Ying Wai Li
- Los Alamos National Laboratory
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Wojciech H Zurek
- Los Alamos Natl Lab
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Inferring Low-rank Energy-based Models and the Renormalization Group
ORAL
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Presenters
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Cheyne Weis
- University of Chicago
- U Chicago
Authors
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Cheyne Weis
- University of Chicago
- U Chicago
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Kyle Bojanek
- University of Chicago
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Stephanie E Palmer
- University of Chicago
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Peter B Littlewood
- University of Chicago
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Bidirectional Nonlinear Optical Tomography: Unbiased Characterization of Off- and On-Chip Coupling Efficiencies
ORAL
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Publication: arXiv:2510.13110
Presenters
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Bo-Han Wu
- University of Hawaii at Manoa
Authors
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Bo-Han Wu
- University of Hawaii at Manoa
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Mahmoud Jalali Mehrabad
- Massachusetts Institute of Technology
- MIT
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Dirk Englund
- Massachusetts Institute of Technology
- MIT
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Is Grokking a Computational Glass Relaxation?
ORAL
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Publication: [1] Yang, E., Zhang, X., Shang, Y., & Zhang, G. (2025). High-entropy Advantage in Neural Networks' Generalizability. arXiv:2503.13145. In Revision.
[2] Zhang, X., Shang, Y., Yang, E., & Zhang, G. (2025). Is Grokking a Computational Glass Relaxation? arXiv:2505.11411. Advances in Neural Information Processing Systems, 2025. (Accepted as Spotlight)Presenters
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Entao Yang
- Air Liquide USA
Authors
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Entao Yang
- Air Liquide USA
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Xiaotian Zhang
- City University of Hong Kong
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Yue Shang
- University of Pennsylvania
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Ge Zhang
- City Univ of Hong Kong
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Statistical analysis of neural network structures for the Iris dataset
ORAL
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Presenters
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Xiguang Yang
- University of Georgia
Authors
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Xiguang Yang
- University of Georgia
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Michael Bachmann
- University of Georgia
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Exact solution of the frustrated Potts model with next-nearest-neighbor interactions in one dimension via AI bootstrapping
ORAL
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Publication: Weiguo Yin, Phys. Rev. B 112, 094424 (2025). DOI: https://doi.org/10.1103/y5vc-3t6q
Presenters
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Weiguo Yin
- Brookhaven National Laboratory (BNL)
Authors
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Weiguo Yin
- Brookhaven National Laboratory (BNL)
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Semantic Chunking and the Entropy of Natural Language
ORAL
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Presenters
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Weishun Zhong
- Institute for Advanced Study
Authors
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Weishun Zhong
- Institute for Advanced Study
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Tankut Can
- Emory University
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Mikhail Katkov
- Institute for Advanced Study, Princeton and Weizmann Institute of Science
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Misha Tsodyks
- Institute for Advanced Study, Princeton and Weizmann Institute of Science
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Stochastic Resetting of Reinforcement Learning Agents
ORAL
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Presenters
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Jello Zhou
- Stanford University
Authors
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Jello Zhou
- Stanford University
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David J Schwab
- The Graduate Center, City University of New York
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Wave Ngampruetikorn
- University of Sydney
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Expressivity of first-order phase transitions
ORAL
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Presenters
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Aditya Gandotra
- University of Chicago
Authors
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Aditya Gandotra
- University of Chicago
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Mason N Rouches
- University of Chicago
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Constantine G Evans
- Maynooth University
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Arvind Murugan
- University of Chicago
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Learning Order: Can Neural Networks Discover Phase Transitions Without Symmetry Functions?
ORAL
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Publication: [1] Carina Karner "Variational autoencoders can detect phase signatures from raw trajectory data", in preparation, 2026
Presenters
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Carina Karner
- Vienna University of Technology
Authors
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Carina Karner
- Vienna University of Technology
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Abstract Withdrawn
ORAL · Withdrawn
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