Physics-Informed Diffusion Models

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Overview

This field studies how to make diffusion models generate or recover data that obey physical laws, especially when observations are sparse, noisy, or incomplete. Common approaches add PDE residuals, conservation laws, or boundary conditions to training, or enforce constraints during sampling with differentiable solvers, projections, and measurement guidance. Applications include scientific field generation and forecasting, inverse problems such as imaging and seismic reconstruction, and physically plausible motion. A central tension is improving physical consistency without distorting the data distribution, while keeping inference efficient and uncertainty reliable.

Latest papers

CardsList

51 papers8 papers in the last four weeks, up 167% on the four weeks before. 0.0% of all new papers.

  1. Vector Field Synthesis with Sparse Streamlines Using Diffusion Model

    Apr 10, 2026Nguyen K. Phan, Ricardo Morales, Sebastian D. Espriella +1Physics-Informed Diffusion Models

    University of Houston

  2. PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics

    Apr 10, 2026Min Young Baeg, Yoon-Yeong KimSpatiotemporal ForecastingLong-Term Time Series Forecasting

  3. Single-Stage Signal Attenuation Diffusion Model for Low-Light Image Enhancement and Denoising

    Apr 7, 2026Ying Liu, Junchao Zhang, Caiyun WuLow-Light Image EnhancementDiffusion Models for Image Restoration

    School of Aeronautics and Astronautics, Central South University, Changsha 410083, China · Hunan Provincial Key Laboratory of Optic-Electronic Intelligent Measurement and Control, Changsha 410083, China

  4. PhaseFlow4D: Physically Constrained 4D Beam Reconstruction via Feedback-Guided Latent Diffusion

    Apr 4, 2026Alexander Scheinker, Alexander Plastun, Peter Ostroumov4D ReconstructionPhysics-Informed Diffusion Models

    Los Alamos National Laboratory Los Alamos 87545, NM, USA · Facility for Rare Isotopes Beams Michigan State University, East Lansing, MI 48824, USA

  5. MMPhysVideo: Physically Plausible Video Generation Through Joint RGB-Perception Modeling

    Apr 3, 2026Shubo Lin, Xuanyang Zhang, Wei Cheng +3Physical Consistency in Video GenerationVideo Diffusion Models

    State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA · School of Artificial Intelligence, University of Chinese Academy of Sciences · StepFun +2

  6. PAD-Hand: Physics-Aware Diffusion for Hand Motion Recovery

    Mar 27, 2026Elkhan Ismayilzada, Yufei Zhang, Zijun Cui3D Hand Pose EstimationPhysics-Informed Diffusion Models

    Michigan State University · Independent Researcher

  7. RadioDiff-FS: Physics-Informed Manifold Alignment in Few-Shot Diffusion Models for High-Fidelity Radio Map Construction

    Mar 19, 2026Xiucheng Wang, Zixuan Guo, Nan ChengRadio Propagation ModelingPhysics-Informed Diffusion Models

    State Key Laboratory of ISN and School of Telecommunications Engineering, Xidian University, Xi’an 710071, China · School of Physics, Xidian University, Xi’an 710071, China

  8. Robust Physics-Guided Diffusion for Full-Waveform Inversion

    Mar 17, 2026Jishen Peng, Enze Jiang, Zheng Ma +1Diffusion-Based Inverse ProblemsInverse Problems

    School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China · Institute of Natural Sciences, MOE-LSC, Shanghai Jiao Tong University, Shanghai, China · Qing Yuan Research Institute, Shanghai Jiao Tong University, Shanghai, China +2

  9. Learning Latent Proxies for Controllable Single-Image Relighting

    Mar 16, 2026Haoze Zheng, Zihao Wang, Xianfeng Wu +5Physics-Informed Diffusion ModelsControllable Image Generation

    HKUST · HKPolyU · CUHK

  10. Mapping Dark-Matter Clusters via Physics-Guided Diffusion Models

    Mar 15, 2026Diego Royo, Brandon Zhao, Adolfo Muñoz +2AstrophysicsDiffusion-Based Inverse Problems

    Universidad de Zaragoza–I3A, Spain · California Institute of Technology, USA

  11. CT-Conditioned Diffusion Prior with Physics-Constrained Sampling for PET Super-Resolution

    Mar 14, 2026Liutao Yang, Zi Wang, Peiyuan Jing +5Medical Image Super-ResolutionPET/CT Imaging

    Department of Bioengineering and Imperial-X, Imperial College London, London, U.K. · College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China. · School of Engineering, Zurich University of Applied Sciences, Winterthur, Switzerland. +3

  12. PhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization

    Mar 13, 2026Yangsong Zhang, Anujith Muraleedharan, Rikhat Akizhanov +5Human Motion GenerationRobot Motion Generation

    Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) · LIGM, École des Ponts, IP Paris, Univ Gustave Eiffel, CNRS · École polytechnique fédérale de Lausanne (EPFL)

  13. Differentiable Stochastic Traffic Dynamics: Physics-Informed Generative Modelling in Transportation

    Mar 10, 2026Wuping XinPhysics-Informed Generative ModelingTraffic Flow Estimation

    Caliper Corporation

  14. Physics-Informed Diffusion Model for Generating Synthetic Extreme Rare Weather Events Data

    Mar 6, 2026Marawan Yakout, Tannistha Maiti, Monira Majhabeen +1Synthetic Data GenerationSynthetic Data Augmentation

    Department of Computer Science, University of London, London · Deepkapha AI Lab, Assen, The Netherlands

  15. Particle-Guided Diffusion for Gas-Phase Reaction Kinetics

    Mar 5, 2026Andrew Millard, Henrik PedersenReaction-Diffusion SystemsPhysics-Informed Diffusion Models

    Department of Computer and Information Science, Linköping University, Linköping, Sweden · Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden

  16. Zero-shot Low-Field MRI Enhancement via Diffusion-Based Adaptive Contrast Transport

    Mar 2, 2026Muyu Liu, Chenhe Du, Xuanyu Tian +5Magnetic Resonance ImagingDiffusion Models for Image Restoration

    School of Information Science and Technology, ShanghaiTech University, Shanghai, China · School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

  17. Phys-Diff: A Physics-Inspired Latent Diffusion Model for Tropical Cyclone Forecasting

    Feb 28, 2026Lei Liu, Xiaoning Yu, Kang Chen +4Tropical Cyclone Intensity ForecastingWeather Forecasting

    University of Science and Technology of China, Hefei, China · Hefei University of Technology, Hefei, China

  18. Diffusion-Based Low-Light Image Enhancement with Color and Luminance Priors

    Feb 27, 2026Xuanshuo Fu, Lei Kang, Javier Vazquez-CorralLow-Light Image EnhancementConditional Diffusion Models

    Computer Vision Center, Cerdanyola del Vallès, Spain and Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain

  19. Physics-Consistent Diffusion for Efficient Fluid Super-Resolution via Multiscale Residual Correction

    Feb 25, 2026Zhihao Li, Shengwei Dong, Chuang Yi +5Physics-Informed Diffusion ModelsImage Super-Resolution

    The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · SandGold AI Research, Guangzhou, China · The Hong Kong University of Science and Technology, Hong Kong SAR, China +1

  20. Learning Flow Distributions via Projection-Constrained Diffusion on Manifolds

    Feb 19, 2026Noah Trupin, Rahul Ghosh, Aadi JangidConstrained Generative ModelingPhysics-Informed Diffusion Models

    Department of Computer Science, Purdue University

  21. 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