Physics-Informed ML

ML: Machine Learning

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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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Learning Interpretable PDE Representations for Generative Reconstructions with Structured Sparsity
Apr 26, 2026Valerie Tsao, Nathaniel Chaney, Manolis VeveakisPhysics-Informed Diffusion Models Sparse Recovery
Department of Civil & Environmental Engineering, Duke University, NC, USA.
WISE-FM:Operation-Aware, Engineering-Informed Foundation Model for Multi-Task Well Design
Apr 26, 2026Carine de Menezes Rebello, Anderson Rapello dos Santos, Idelfonso B. R. NogueiraSurrogate Modeling Multi-Task Learning
Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway · Petróleo Brasileiro S.A. (PETROBRAS), Wells/Well Engineering, Rio de Janeiro, Brazil
An architectural capacity ceiling, not a barren plateau: why a fixed-encoding variational quantum circuit cannot fit the Lorenz-63 attractor
Apr 26, 2026Tushar PandeyVariational Quantum Circuits Physics-Informed ML
Texas A&M University, College Station, TX 77843, USA
QuietWalk: Physics-Informed Reinforcement Learning for Ground Reaction Force-Aware Humanoid Locomotion Under Diverse Footwear
Apr 26, 2026Hanze Hu, Luying Feng, Silu Chen +6Humanoid Robot Locomotion Robot Locomotion
Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data
Apr 26, 2026Ru Geng, Panayotis Kevrekidis, Yixian Gao +2Dynamical Systems Graph Structure Learning
School of Mathematics and Statistics, Changchun University, Changchun, 130022, China · Department of Mathematics and Statistics, University of Massachusetts, Amherst, 01003, MA, USA · Department of Physics, University of Massachusetts, Amherst, 01003, MA, USA +2
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
Apr 26, 2026Sifan Wang, Shawn Koohy, Yiping Lu +1PDE Solving Physics-Informed ML
Institute for Foundations of Data Science, Yale University · Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania · Industrial Engineering & Management Science, Northwestern University
Interpretable Physics-Informed Load Forecasting for U.S. Grid Resilience: SHAP-Guided Ensemble Validation in Hybrid Deep Learning Under Extreme Weather
Apr 26, 2026Md Abubakkar, Sajib Debnath, Md. Uzzal MiaHybrid CNN-Transformer Architectures Time Series Forecasting
Dept. of Computer Science, Midwestern State University, Dallas, TX, USA · O&M Analytics, AES Clean Energy, The AES Corporation, Louisville, CO, USA · Dept. of Information and Communication Engineering, Pabna University of Science and Technology, Bangladesh
GeoCert: Certified Geometric AI for Reliable Forecasting
Apr 25, 2026Regina Zhang, Zongru Li, Honggang Wen +4Neural Network Verification Time Series Forecasting
Department of Biomedical Informatics & Data Science, Yale University, US · School of Computing and Data Science, Nanyang Technological University, Singapore. · Department of Computer Science, The University of Hong Kong, Hong Kong SAR +1
Physics-Informed Temporal U-Net for High-Fidelity Fluid Interpolation
Apr 25, 2026Eshwar R. A., Nevin Mathew Thomas, Nehal G +1U-Net Video Frame Interpolation
Department of Computer Science Engineering, PES University - Electronic City Campus, Bangalore 560100, India.
Collocation-based Robust Physics Informed Neural Networks for time-dependent simulations of pollution propagation under thermal inversion conditions on Spitsbergen
Apr 24, 2026Leszek Siwik, Maciej Sikora, Natalia Leszczyńska +7Neural PDE Solvers Air Quality Prediction
AGH University of Krakow, Faculty of Computer Science, Al. Mickiewicza 30, Kraków, 30-059, Poland · Medical University of Silesia-Katowice, Faculty of Medical Sciences, ul. Poniatowskiego 15, Katowice, 40-055, Poland · The University Centre in Svalbard, Longyearbyen, Box 156 N-9171, Longyearbyen, Norway +4
Information-Theoretic Geometry Optimization and Physics-Aware Learning for Calibration-Free Magnetic Localization
Apr 24, 2026Wenxuan Xie, Yuelin Zhang, Qingpeng Ding +4Sim-to-Real Transfer Wireless Localization
Department of Mechanical and Automation Engineering and T Stone Robotics Institute, The Chinese University of Hong Kong, Hong Kong.
Transferable Physics-Informed Representations via Closed-Form Head Adaptation
Apr 23, 2026Jian Cheng Wong, Isaac Yin Chung Lai, Pao-Hsiung Chiu +3Representation Learning PDE Solving
Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore · National University of Singapore (NUS), Singapore · Indian Institute of Technology Goa (IIT Goa), India +1
A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
Apr 23, 2026Mohammad Mahdi Abedi, David Pardo, Tariq AlkhalifahNeural PDE Solvers PDE Solving
University of the Basque Country (UPV/EHU), Department of Mathematics, Spain · Basque Center for Applied Mathematics (BCAM), Bilbao, Spain · Ikerbasque, Basque Foundation for Science, Bilbao, Spain +1
CO $_2$ sequestration hybrid solver using isogeometric alternating-directions and collocation-based robust variational physics informed neural networks (IGA-ADS-CRVPINN)
Apr 22, 2026Askold Vilkha, Tomasz Służalec, Marcin Łoś +1Neural PDE Solvers PDE Solving
AGH University of Krakow, Faculty of Computer Science, Al. Mickiewicza 2026 30, Kraków, 30-059, Poland
Physics-Informed Conditional Diffusion for Motion-Robust Retinal Temporal Laser Speckle Contrast Imaging
Apr 22, 2026Qian Chen, Yuehao Chen, Qiang Wang +3Image Reconstruction Physics-Informed ML
Department of Biomedical Engineering, Peking University, Beijing, China · Institute of Medical Technology, Peking University, Beijing, China · Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China +2
Physics-Enhanced Deep Learning for Proactive Thermal Runaway Forecasting in Li-Ion Batteries
Apr 22, 2026Salman Khan, Syed Sajid Ullah, Muhammad Zunair Zamir +3Recurrent Neural Networks Physics-Informed ML
A Hybrid Windkessel-Neural Approach for Improved Noninvasive Blood Pressure Monitoring
Apr 21, 2026Vaibhav Gollapalli, Aniruth AnanthanarayananPhysics-Informed ML Wearable Health Monitoring
Department of Physics University of North Texas Denton, United States of America
Physics-Informed Neural Networks for Biological $2\mathrm{D}{+}t$ Reaction-Diffusion Systems
Apr 20, 2026William Lavery, Jodie A. Cochrane, Christian Olesen +3Dynamical Systems PDE Discovery
Dept. of Information Technology Uppsala University Uppsala, Sweden · Dept. of Medical Genetics Oslo University Hospital Oslo, Norway · Dept. of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, USA +1
Physics-Informed Neural Networks: A Didactic Derivation of the Complete Training Cycle
Apr 20, 2026Abdeladhim TahimiBackpropagation Physics-Informed ML
Campus de Engenharias e Ciências Agrárias (CECA), Universidade Federal de Alagoas (UFAL), Rio Largo, Alagoas, 57100-000, Brazil
Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems
Apr 20, 2026Hanfeng Zhai, Hongtao Qiao, Hassan Mansour +1Neural Surrogate Modeling Physics-Informed ML
Department of Mechanical Engineering, Stanford University, Stanford, CA · Mitsubishi Electric Research Laboratories, Cambridge, MA
Dissipative Latent Residual Physics-Informed Neural Networks for Modeling and Identification of Electromechanical Systems
Apr 20, 2026Youyuan Long, Gokhan Solak, Arash AjoudaniDynamical Systems Residual Learning
Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, 16163 Genoa, Italy
Machine Learning Hamiltonian Dynamical Systems with Sparse and Noisy Data
Apr 19, 2026Vedanta Thapar, Abhinav GuptaNonlinear System Identification Recurrent Neural Networks
The Mathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom · Center for Theoretical Physics, St. Stephen’s College, University of Delhi, Delhi 110007, India
What Physics do Data-Driven MoCap-to-Radar Models Learn?
Apr 19, 2026Kevin Chen, Kenneth W. Parker, Anish AroraPhysics-Informed ML
Computer Science & Engineering The Ohio State University Columbus, Ohio · Unaffiliated Waterford, Virginia
Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles
Apr 18, 2026Khemraj Shukla, Zongren Zou, Theo Kaeufer +2Uncertainty Quantification Deep Ensembles
Division of Applied Mathematics, Brown University, Providence, RI, USA · Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA · Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
Physics-Informed Tracking (PIT)
Apr 18, 2026Emil Hovad, Allan Peter Engsig-KarupPoint Tracking Visual Object Tracking
Department of Applied Mathematics and Computer Science (DTU Compute) Technical University of Denmark
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
Apr 18, 2026Yixuan WangPDE Solving Kolmogorov-Arnold Networks
CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California · [math.NA]
Zero-Shot Scalable Resilience in UAV Swarms: A Decentralized Imitation Learning Framework with Physics-Informed Graph Interactions
Apr 17, 2026Huan Lin, Lianghui DingMulti-Robot Systems Swarm Robotics
Institute of Image Communication and Network Engineering, School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China
Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks
Apr 17, 2026Hyeongmeen Baik, Hamed Poursiami, Maryam Parsa +1Parameter Estimation Predictive Maintenance
University of Wisconsin–Madison Madison, Wisconsin, USA · George Mason University Fairfax, Virginia, USA
PINNACLE: An Open-Source Computational Framework for Classical and Quantum PINNs
Apr 17, 2026Shimon Pisnoy, Hemanth Chandravamsi, Ziv Chen +4Neural PDE Solvers PDE Surrogate Modeling
†Faculty of Mechanical Engineering, Technion Israel Institute of Technology, Haifa, Israel. · ‡Corresponding author. · §The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering, Technion Israel Institute of Technology, Haifa, Israel. +2
Physics-Informed Neural Networks with Learnable Loss Balancing and Transfer Learning
Apr 17, 2026Reza PirayeshshirazinezhadSelf-Supervised Learning Adaptive Loss Weighting
Texas A&M University College Station, TX, USA

Apr 26, 2026, cs.LGJ/K move · Enter open · S save

Learning Interpretable PDE Representations for Generative Reconstructions with Structured Sparsity

Valerie Tsao, Nathaniel Chaney, Manolis Veveakis

Department of Civil & Environmental Engineering, Duke University, NC, USA.

Physics-Informed Diffusion Models Sparse Recovery Latent Diffusion Models Physics-Informed ML Diffusion-Based Inverse Problems PDE Inverse Problems+1

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Scientific measurements are often bottlenecked by suboptimal conditions, whether that be noise, incomplete spatial coverage, or limited resolution, rendering accurate field reconstruction a difficult task. We introduce LatentPDE, a latent diffusion framework designed to simultaneously resolve sparse-observation reconstruction and super-resolution. While existing physics-guided diffusion models typically rely on soft loss penalties or uninterpretable representations, our approach enforces physical compliance by constructing an inherently interpretable latent space. Specifically, we parameterize the latent variables directly as the coefficients and source terms of an assumed governing PDE. In doing so, LatentPDE is able to reliably reconstruct dynamics across highly disparate and structured data gaps. Empirical results on diverse configurations demonstrate that our model achieves high-fidelity recovery at any desired resolution while also tracking the underlying predictive uncertainty.

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