Physics-Informed ML

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60 papers in the last four weeks, up 131% on the four weeks before. 0.6% of all new papers.

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  1. Machine Learning Meets High-Energy Nuclear Physics: From Pattern Recognition to Physics-Integrated Discovery

    Oct 8, 2026Xun Chen, Weiyao Ke, Yu-Gang Ma +2High-Energy PhysicsPhysics-Informed ML

    School of Nuclear Science and Technology, University of South China, Hengyang 421001, China · INFN — Istituto Nazionale di Fisica Nucleare — Sezione di Bari, Via Orabona 4, 70125 Bari, Italy · Key Laboratory of Quark and Lepton Physics (MOE) & Institute of Particle Physics, Central China Normal University, Wuhan, Hubei 430079, China +6

  2. Ghost tasking for parametrized Gaussian Processes solving linear differential equations

    Oct 8, 2026Johanna Moser, Christopher Albert, Sascha RanftlGaussian ProcessesPhysics-Informed ML

  3. Uncovering and Fixing Collider Bias in Bayesian PINNs

    Oct 8, 2026Michael Obermayr, Robert PeharzPhysics-Informed MLBayesian Inverse Problems

    TU Graz

  4. Cova-PINN: Cross-Domain Conservation Physics-Informed Neural Network for Fluid-Solid Conjugate Heat Transfer in Complex Geometries

    Oct 8, 2026Weizheng Zhang, Xunjie Xie, Hao Pan +1Physics-Informed MLNeural PDE Solvers

    Shandong University · Tsinghua University

  5. Gen-PINNs: Generative Adversarial Physics Informed Neural Networks for solving partial differential equations

    Oct 7, 2026Muhammad M. Akmal, Kamy Sepehrnoori, Michael J. PyrczPDE SolvingPhysics-Informed ML

    Hilderbrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin · Department of Earth and Planetary Sciences, The University of Texas at Austin

  6. Physics-Aligned Electronic Ground-State Learning Improves Generalization

    Oct 7, 2026Eike S. Eberhard, Xaver Kainz, Viktor Kotsev +2Physics-Informed MLOOD Generalization

    Technical University of Munich (TUM) · Munich Data Science Institute (MDSI) · Munich Center for Machine Learning (MCML) +1

  7. ProtocolMatch: Protocol-Dependent Model Selection for Scientific Dynamics Forecasting

    Oct 7, 2026Lu Wei, Yufeng Wang, Haibin LingModel SelectionPhysics-Informed ML

    Stony Brook University · Westlake University

  8. Physics-Informed Neural Plasticity: PDE Solvers That Reshape Themselves

    Oct 7, 2026Chun-Wun Cheng, Bingcheng Hu, Angelica I. Aviles-RiveroNeural PDE SolversPDE Solving

    Shanghai Normal University · YMSC, Tsinghua University

  9. Domain-informed Adaptive Sampling for Generalizable PINNs in Metal Additive Manufacturing via Conditional Flow Matching

    Oct 6, 2026Hyeonsu Lee, Jihoon JeongAdaptive SamplingPhysics-Informed ML

    Wm Michael Barnes ’64 Department of Industrial and Systems Engineering Texas A&M University College Station, TX 77843, USA

  10. A Physics-Guided Transformer Framework for Electromigration Analysis in Multi-Segment Interconnects

    Oct 5, 2026Pavlos Stoikos, Anuj Pathania, George FlorosNeural Surrogate ModelingTransformer

    Dept. of Electrical and Computer Engineering University of Thessaly, Greece · University of Amsterdam Amsterdam, The Netherlands · Dept. of Electronic and Electrical Engineering, Trinity College Dublin, Ireland

  11. IGA-KAN: Isogeometric Analysis with Physics-Informed Closed-Form Kolmogorov-Arnold Networks for Forward and Inverse PDEs

    Oct 5, 2026Sima Naraghi, Kourosh Parand, Amirhossein Sadr +1Neural PDE SolversKolmogorov-Arnold Networks

    Department of Applied Mathematics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran · Department of Computer and Data Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran · Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran +1

  12. OCL-PDE: A Generative Framework for PDE Inverse Problems with Observation-Complementary Latents

    Oct 5, 2026Ding Yang, Chuqi Chen, Chang Ma +1Physics-Informed Generative ModelingPDE Operator Learning

    Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong · Department of Mathematics, University of Michigan, Ann Arbor, USA · Department of Materials, The Hong Kong University of Science and Technology, Hong Kong +1

  13. Parameter Estimation in Machining Dynamics with Regenerative Delay and Nonsmooth Friction using Physics-Informed Neural Networks

    Oct 5, 2026Meiyazhagan Jaganathan, Vikram Pakrashi, Aasifa RounakDynamical SystemsParameter Estimation

    UCD Centre for Mechanics, Dynamical Systems and Risk Laboratory, School of Mechanical and Materials Engineering, University College Dublin, D04 V1W8, Dublin, Ireland

  14. R1A-PC: Physics-Guided Electromagnetic Inversion of Three-Dimensional Human Point Clouds in Complex Static Environments

    Oct 4, 2026Xudong Yuan, Ruyun Xu, Jingtai Yang +13D ReconstructionPoint Cloud Surface Reconstruction

    School of Mathematics and Statistics, Changchun University of Science and Technology, Changchun, China.

  15. Component-Level Evaluation of Adaptive PINN Training for CFD-Oriented Crystal Growth Simulation

    Oct 4, 2026Niruta Chapagain, Rohit Raj, Bertwin Kurisinkal Shine +1Neural PDE SolversPDE Surrogate Modeling

    University of Europe for Applied Sciences Potsdam, Germany · Vienna, Austria · Technische Universität Chemnitz Chemnitz, Germany +1

  16. Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering

    Oct 1, 2026Michael Baldea, Linda J. Broadbelt, Marianthi G. Ierapetritou +17Scientific MLPhysics-Informed ML

    McKetta Department of Chemical Engineering and Oden Institute for Chemical Engineering and Sciences, The University of Texas at Austin, Austin, TX 78731, USA · Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA · Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA +13

  17. PhysDEM: Physics-Defined Energy-Matching Diffusion for Spatiotemporal Field Generation under Scarce Measurements

    Oct 1, 2026Zhenyu Liang, Yining Huang, Yubo Zhao +1Physics-Informed Diffusion ModelsPhysics-Informed Generative Modeling

    HKUST · UT Austin

  18. PACT: End-to-End Learning of Human Pose, Contacts, and Forces from Video

    Sep 30, 2026Rikhat Akizhanov, Yangsong Zhang, Nikolai Kaliazin +5Human Pose Estimation3D Human Reconstruction

    MBZUAI · ETH Zürich · EPFL

  19. PINNing the pion: conformal deep learning for Fπ(s)F_π(s) and the (g−2)μ(g-2)_μ hadronic contribution

    Sep 30, 2026Mayank Goel, Subhadip Mitra, Monalisa PatraHigh-Energy PhysicsPhysics-Informed ML

    Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India

  20. Physics-Informed Method of Group Data Handling: Adaptive Construction of Functional Representations with an Application to the Navier-Stokes Equations

    Sep 30, 2026Mykhailo MininNeural PDE SolversPhysics-Informed ML

    JSC KIEP, Kyiv, Ukraine

  21. PE-EK-PINN: Physics Embedding with Evolving Kernel for Scalable Physics-Informed Neural Networks

    Sep 29, 2026Huiwen Zhang, Feng Ye, Chu MaNeural PDE SolversPhysics-Informed ML

    Department of Electrical & Computer Engineering Madison, WI, 53706, USA

  22. GAC-PINN: Geometry-Adaptive and Constraint-Enhanced Physics-Informed Neural Networks

    Sep 28, 2026Yanxin Zhang, Yong Zhang, Houbiao LiNeural PDE SolversPhysics-Informed ML

    University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

  23. Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics

    Sep 28, 2026Pradyumn Singh Sikarwar, Vishal Sharma, Gaurav BhutaniNeural PDE SolversPhysics-Informed ML

    School of Mechanical and Materials Engineering, Indian Institute of Technology Mandi, India

  24. PDE-JEPA: Predictive Representation Learning of Latent Dynamics Modeling for Parametric PDEs

    Sep 28, 2026Zhentao Tan, Jianrong Zhang, Ruijie Quan +1Latent Dynamics ModelingJoint-Embedding Predictive Architecture

    Zhejiang University.

  25. When Known Physics Helps Neural PDE Models: Residual Constraints Out-Regularize Generic Priors for Nonlinear Dynamics

    Sep 27, 2026Zahra Farazpay, Aniruddha BoraPDE Surrogate ModelingPhysics-Informed ML

    Department of Physics Louisiana Tech University Ruston, LA, USA · Department of Computer Science Texas State University San Marcos, TX, USA

  26. PI-NOMT: Physics-Informed Neural Optimal Mass Transport for Brain Fluid Dynamics

    Sep 27, 2026Mehmet Emin Acar, Vahit Bugra Yesilkaynak, Helene Benveniste +1Physics-Informed MLPDE Inverse Problems

    Istanbul Technical University, Faculty of Computer and Informatics Engineering, AI and Data Engineering Department, Istanbul, Turkiye · Yale University, School of Medicine, New Haven, CT, USA

  27. From Grey-Box to Green-Box: When can Physics-Informed Machine Learning Reduce Carbon Footprints in Structural Health Monitoring?

    Sep 27, 2026Daisy R. Bradley, Nathan A. Hinchliffe, Daniel J. Pitchforth +2Energy-Efficient MLPhysics-Informed ML

    Dynamics Research Group, University of Sheffield, Sheffield, UK

  28. The limits of exactness: On the failure of automatic differentiation in physics-informed machine learning

    Sep 27, 2026Ameya D. JagtapAutomatic DifferentiationPDE Surrogate Modeling

    Aerospace Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA

  29. Physics-Guided Multi-Objective Deep Learning for Ultrasound RF Data Interpolation in Resource-Constrained Imaging

    Sep 23, 2026Luoyuan Zhang, Yiyang You, Ananya Tandri +4Physics-Guided Image RestorationImage Reconstruction

    University of North Carolina at Chapel Hill, Chapel Hill, NC, USA · Johns Hopkins University, Baltimore, MD, USA

  30. Physics-Informed Self-Supervised Learning for Joint Wire Calibration and Interaction Position Reconstruction in Multi-Wire Parallel Plate Avalanche Counters

    Sep 23, 2026Antoine Lemasson, Maurycy RejmundSelf-Supervised LearningPhysics-Informed ML

    GANIL, CEA/DRF - CNRS/IN2P3, Bd Henri Becquerel, BP 55027, F-14076 Caen Cedex 5, France.