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. Neural network-driven domain decomposition for efficient solutions to the Helmholtz equation

    Nov 19, 2025Victorita Dolean, Daria Hrebenshchykova, Stéphane Lanteri +1Neural PDE SolversPDE Solving

    Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands · Atlantis project-team, Inria Research Center at Université Côte d’Azur, France · MACARON project-team, Université de Strasbourg, CNRS, Inria, IRMA, France

  2. Hard-constraint physics-residual networks for hydrogen crossover prediction and high-pressure extrapolation in PEM water electrolysis

    Nov 8, 2025Yong-Woon Kim, Jihyeok Lee, Chulung Kang +1Neural Surrogate ModelingPhysics-Informed ML

    Department of Computer Engineering, Jeju National University, Jeju, 63243, South Korea · Faculty of Applied Energy System, Jeju National University, Jeju, 63243, South Korea · Department of Mechanical System Engineering, Jeju National University, Jeju, 63243, South Korea +1

  3. Physics-Informed Neural Networks for Speech Production

    Nov 1, 2025Kazuya Yokota, Ryosuke Harakawa, Masaaki Baba +1Speech ProcessingPhysics-Informed ML

    Department of Mechanical Engineering, Nagaoka University of Technology, 1603-1, Kamitomioka, Nagaoka, Niigata, Japan · Department of Electrical, Electronics and Information Engineering, Nagaoka University of Technology

  4. LieSolver: PDE-Constrained Learning for IBVPs via Lie Symmetries

    Oct 29, 2025René P. Klausen, Ivan Timofeev, Jonas Naujoks +4Neural PDE SolversPDE Solving

    Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany · Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Germany · BIFOLD Berlin Institute for the Foundations of Learning and Data, Berlin, Germany +1

  5. Inverse Problem for Partial Differential Equations with Jump Discontinuities in Coefficients by Two-stage Physics-Informed Deep Learning and Statistical Mixture Models

    Oct 16, 2025Zhikun Zhang, Guanyu Pan, Xiangjun Wang +2Bayesian Mixture ModelsPhysics-Informed ML

    School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China · School of Mathematics and Computational Science, Xiangtan University, Xiangtan 411105, China · SandGold AI Research, Guangzhou 510642, China +3

  6. Neural non-canonical Hamiltonian dynamics for long-time simulations

    Oct 2, 2025Clémentine Courtès, Emmanuel Franck, Michael Kraus +2Dynamical SystemsNonlinear System Identification

    IRMA, MACARON · Institut de Recherche Mathématique Avancée, UMR 7501 Université de Strasbourg et CNRS, 7 rue René Descartes 672000 Strasbourg, France. · INRIA Nancy-Grand Est, MACARON Project, Strasbourg, France. +5

  7. MAD-PINN: A Decentralized Physics-Informed Machine Learning Framework for Safe and Optimal Multi-Agent Control

    Sep 28, 2025Manan Tayal, Aditya Singh, Shishir Kolathaya +1Multi-Agent ControlConstrained Optimization

    Center for Cyber-Physical Systems, Indian Institute of Science, Bangalore, India · Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, USA · Department of Aeronautics and Astronautics, Stanford University, USA

  8. Physics-informed GNN for medium-high voltage AC power flow with edge-aware attention and line search correction operator

    Sep 26, 2025Changhun Kim, Timon Conrad, Redwanul Karim +6Efficient Neural Network InferenceGraph Attention Networks

    Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  9. A Flow-rate-conserving CNN-based Domain Decomposition Method for Blood Flow Simulations

    Sep 19, 2025Simon Klaes, Axel Klawonn, Natalie Kubicki +4PDE SolvingPDE Surrogate Modeling

    Department of Mathematics and Computer Science, University of Cologne, Germany · Center for Data and Simulation Science, University of Cologne, Germany · Institute for Advanced Simulation (IAS-2), Forschungszentrum Jülich, Germany +1

  10. Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks for the Poisson Equation

    Aug 29, 2025Bangti Jin, Longjun WuNeural PDE SolversPDE Solving

    Department of Mathematics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, P.R. China

  11. InSituRes: A Physics-Informed Same-Grid Model for Enhanced Dynamic X-ray Micro-CT Reconstructions

    Aug 25, 2025Qinyi Tian, Andrea Bisciotti, Soniya Tiwari +2Image RestorationPhysics-Informed ML

    Department of Civil & Environmental Engineering, Duke University, Durham, North Carolina, 27708, USA · Department of Physics and Earth Sciences, University of Ferrara, Via Saragat 1, Ferrara 44141, Italy · Department of Mechanical Engineering & Materials Science, Duke University, Durham, North Carolina, 27708, USA

  12. Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

    Aug 5, 2025Jan Tauberschmidt, Sophie Fellenz, Sebastian J. Vollmer +1Physics-Informed Generative ModelingFlow Matching

    DSA, German Research Center for Artificial Intelligence (DFKI) · Department of Computer Science, University of Kaiserslautern–Landau (RPTU) · Department of Mathematics, Imperial College London

  13. DPG loss functions for learning parameter-to-solution maps by neural networks

    Jun 23, 2025Pablo Cortés Castillo, Wolfgang Dahmen, Jay GopalakrishnanPDE SolvingPDE Surrogate Modeling

  14. GeNeRT: A Physics-Informed Approach to Intelligent Wireless Channel Modeling via Generalizable Neural Ray Tracing

    Jun 23, 2025Kejia Bian, Meixia Tao, Shu Sun +2Neural Network GeneralizationWireless Communications

    School of Information Science and Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China · Shanghai Innovation Institute, Shanghai 200231, China

  15. Interpretability and Generalization Bounds for Learning Spatial Physics

    Jun 18, 2025Alejandro Francisco Queiruga, Theo Gutman-Solo, Shuai JiangNeural Network GeneralizationMechanistic Interpretability

    OpenAI, San Francisco, CA, USA · Google, Mountain View, CA, USA · Sandia National Laboratories, Albuquerque, NM, USA

  16. Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation

    May 28, 2025Yi Zhang, Peng Wang, Difan ZouPhysics-Informed Diffusion ModelsDiffusion Model Distillation

    Institute of Data Science · Department of Computer and Information Science · Institute of Data Science & School of Computing and Data Science

  17. Accelerating Natural Gradient Descent for PINNs with Randomized Numerical Linear Algebra

    May 16, 2025Ivan Bioli, Carlo Marcati, Giancarlo SangalliNeural PDE SolversGradient Descent

    Department of Mathematics, University of Pavia, Via A. Ferrata 5, 27100 Pavia, Italy · Department of Civil Engineering and Architecture, University of Pavia, Via A. Ferrata 3, 27100 Pavia, Italy · Istituto di Matematica Applicata e Tecnologie Informatiche “E. Magenes”, CNR, Via A. Ferrata 1, 27100 Pavia, Italy

  18. Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy

    May 6, 2025Julian P. Merkofer, Dennis M. J. van de Sande, Alex A. Bhogal +1Normalizing FlowsBayesian Inference

    Eindhoven University of Technology, Eindhoven, The Netherlands · University Medical Center Utrecht, Utrecht, The Netherlands

  19. Residuals Are Not Enough: Limits of Physics-Informed Pre-Training for Scientific Foundation Models

    Mar 24, 2025Serge Kotchourko, Amin Totounferoush, Michael W. Mahoney +1PDE Surrogate ModelingPhysics-Informed ML

    University of Stuttgart, Germany · ICSI, LBNL, and University of California, Berkeley, USA

  20. Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications

    Mar 3, 2025Yuchen Xiang, Zhaolu Liu, Monica Emili Garcia-Segura +12Self-Supervised LearningPhysics-Guided Image Restoration

    Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK · Department of Mathematics, Imperial College London, London, UK · Department of Clinical Neurosciences and NIHR Biomedical Research Centre, University of Cambridge, Cambridge, UK +4

  21. Physics-Informed Support Vector Kernels via Green-Function Analogies and Jackson-Chebyshev Spectral Design

    Feb 16, 2025Nan-Hong Kuo, Renata WongSupport Vector MachinesKernel Methods

    Department of Physics, National Taiwan University, Taipei, Taiwan · Department of Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan · Department of Neurology, Chang Gung Memorial Hospital, Keelung, Taiwan +1