Fluctuation-Dissipation Theorem

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5 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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  1. Do Better Scores Mean Better Physics? Physics-Grounded Explanations for Sim2Real Neural Operators

    Sep 30, 2026Somyajit Chakraborty, Xizhong ChenPhysics SimulationNeural Operators

    State Key Laboratory of Synergistic Chem-Bio Synthesis, Department of Chemical Engineering, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China

  2. An Analytical Theory of Auxiliary Learning

    Sep 24, 2026Federico Milanesio, Alessandro Ingrosso, Matteo OsellaStochastic Gradient DescentFluctuation-Dissipation Theorem

    Department of Physics and INFN University of Turin Via Giuria 1, 10125 Turin, Italy · Donders Centre for Neuroscience Radboud University Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands

  3. Learning to Fluctuate: Statistical Foundations for Causal Tabular Pretraining

    Sep 22, 2026Zhiheng ZhangCausalPretraining

    School of Statistics and Data Science Shanghai University of Finance and Economics

  4. TAP Accuracy Below the Fluctuation Scale and Universal Posterior Geometry in Spherical Linear Models

    Sep 17, 2026Jingbo Liu, Zhiyuan YuRegularityFluctuation-Dissipation Theorem

    Department of Statistics University of Illinois Urbana-Champaign Champaign, IL 61820

  5. Stochastic Gradient Descent over P2

    Sep 11, 2026Maria Oprea, Qin Li, Yunan YangStochastic Gradient DescentStochastic Differential Equations

    Center for Applied Mathematics, Cornell University · Department of Mathematics, University of Wisconsin–Madison, USA · Department of Mathematics, Cornell University, USA

  6. GazeFS: Target-Centered Gaze-Trajectory Forecasting and Stabilization from Gaze-Head History

    Sep 3, 2026Yaozheng Xia, Zaiping Zhu, Bo Pang +4Gaze Target EstimationStabilization

    School of Information Science and Technology, School of Artificial Intelligence, Beijing Forestry University · School of Digital Art, Nanjing University of the Arts · School of Computer Science, Peking University +1

  7. Towards Large-Scale Heterogeneous Data Organization for Scientific Foundation Models: A Nuclear Fusion Case Study

    Aug 27, 2026Nathaniel Chen, Kouroche Bouchiat, Peter Steiner +3Wireless Foundation ModelsNuclear Fusion

    Mechanical and Aerospace Engineering Princeton University Princeton, NJ 08544, USA · Princeton University Princeton, NJ 08544, USA · Princeton Plasma Physics Laboratory Princeton University Princeton, NJ 08544, USA

  8. IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

    Aug 3, 2026Dingwei Zhu, Jiahan Li, Chengjun Pan +22Tool InvocationIcr-Rl

    1Fudan University · 3Peking University · 2Honor Device Co., Ltd.

  9. Geometry-aware Incremental Neural Operator for Long-Horizon PDE prediction

    Jul 31, 2026Jiaquan Zhang, Shuxu Chen, Haifan Meng +6Neural Partial Differential Equation SolversLong-Horizon Forecasting

    School of Information and Software Engineering, UESTC · Electronics and Information Convergence Engineering, KHU · School of Computer Science and Engineering, UESTC +4

  10. Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks

    Jul 29, 2026Shuhei IkemotoBackpropagationNeural Network

    Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

  11. SPECTRA: State-Space Exogenous Context and Temporal-Frequency Resolution Architecture for Probabilistic Energy Forecasting

    Jul 22, 2026Hang Ye, Xinyan Jiang, Yuedong Shi +5Probabilistic ForecastingEnergy Forecasting

    Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China · University of Chinese Academy of Sciences, Beijing 101408, China · School of Physical Science and Technology, Shanghaitech University, Shanghai 201210, China +2

  12. Structured Fluctuations and the Information Dynamics of Self-Maintenance in Growing Neural Cellular Automata

    Jul 14, 2026Atsushi Masumori, Hiroki Sato, Takashi IkegamiNeural Cellular AutomataSelf-Repair

    The University of Tokyo · Atomi University · Alternative Machine Inc.

  13. Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

    Jul 5, 2026Chan Li, Nigel GoldenfeldFluctuation-Dissipation TheoremMean-Field Limit

    Department of Physics, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. · Halıcıoğlu Data Science Institute, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA

  14. Variance Reduction for Stochastic Gradient Generalized Non-reversible Langevin Monte Carlo Algorithms

    Jun 27, 2026Bingye Ni, Xiaoyu Wang, Yingli Wang +1Langevin DynamicsVariance Reduction

    FinTech Thrust, Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, People's Republic of China · School of Mathematical Science, Fudan University, Shanghai, People's Republic of China · Department of Mathematics, Florida State University, Tallahassee, Florida, United States of America

  15. Causal Semantic Alignment for LLM-based Time Series Forecasting

    Jun 6, 2026Kexuan Zhang, Xiaobei Zou, Cesare Alippi +2Zero-Shot ForecastingTime Series

  16. Quantifying Uncertainty In Wide Two-Layer Neural Networks: On The Law Of The Limiting Fluctuation Process

    Jun 4, 2026Arnaud Descours, Arnaud Guillin, Geoffrey Lacour +3Two-Layer Neural NetworksFluctuation-Dissipation Theorem

    LSAF · LMBP · MaIAGE +1

  17. FlashbackCL: Mitigating Temporal Forgetting in Federated Learning

    Jun 2, 2026Mubarak A. Ojewale, Adriana E. Chis, Jorge M. Cortes-Mendoza +2Federated LearningReplay-Based Continual Learning

    Cloud Competency Centre, National College of Ireland, Dublin, Ireland

  18. Memory Uncertainty Relation and Harmonic Memory in Random Recurrent Networks

    May 23, 2026Taichi Haruna, Kohei NakajimaFluctuation-Dissipation TheoremRecurrent Neural Networks

    Department of Information and Mathematical Sciences, School of Arts and Sciences, Tokyo Woman’s Christian University, 2-6-1 Zempukuji, Suginami-ku, Tokyo 167-8585, Japan · Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan

  19. On Stability and Decomposition of Sample Quantiles under Heavy-Tailed Distributions

    May 18, 2026Choudur LakshminarayanQuantile RegressionLong-Tailed Distribution

    School of Business, Stevens Institute of Technology

  20. Scaling Limits of Long-Context Transformers

    May 8, 2026Giuseppe Bruno, Shi Chen, Zhengjiang Lin +2Linear AttentionEfficient Long-Context Inference

  21. Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning

    May 8, 2026Chris Elliott, Daniel MurfetBayesian Neural NetworksBayesian

    Timaeus

  22. Phase Transitions in the Fluctuations of Functionals of Random Neural Networks

    Apr 21, 2026Simmaco Di Lillo, Leonardo Maini, Domenico MarinucciLarge Deviation PrincipleFluctuation-Dissipation Theorem

    RoMaDS - Department of Mathematics, University of Rome Tor Vergata, Rome, Italy

  23. Structural Instability of Feature Composition

    Apr 18, 2026Yunpeng ZhouFeature LearningSteering

    Whiteknights House, Whiteknights, Reading, RG6 6UR