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4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Learning PDE Dynamics between Submanifolds Using Green's Observation Operators
Oct 1, 2026Jan Tauberschmidt, Jephte Abijuru, Samuel Okon +5Heat Diffusion
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany · Rheinland-Pfälzische Technische Universität (RPTU), Kaiserslautern, Germany · University of Manchester, Manchester, United Kingdom
Graph Residual Conjugate Diffusion: SNR-Equalized Heat Flow for Graph Signals
Sep 30, 2026Jinwei Li, Daniel TenbrinckResidual Conditional Diffusion Model Graph Edge Sparsification
Department of Data Science Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, Germany
When Known Physics Helps Neural PDE Models: Residual Constraints Out-Regularize Generic Priors for Nonlinear Dynamics
Sep 27, 2026Zahra Farazpay, Aniruddha BoraNeural Partial Differential Equation Solvers Heat Diffusion
Department of Physics Louisiana Tech University Ruston, LA, USA · Department of Computer Science Texas State University San Marcos, TX, USA
Toward Interpretable Multimodal Fusion: Heat Conduction Modeling for Hyperspectral and LiDAR Joint Classification
Sep 12, 2026Kan Wei, Jiahui Cui, Jing Yao +3Multimodal Fusion Hyperspectral Image
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China · Key Laboratory of Target Cognition and Application Technology, Beijing 100190, China · School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100190, China +3
Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling
Sep 8, 2026Anirudh Avireddy, Manmeet Singh, Shivanshi Singh +4Dynamical Downscaling Land Surface Temperature
Shiv Nadar University, India · Western Kentucky University, USA · Ashoka University, India
Learning Informative Prior with Infinite-Dimensional Continuous Normalizing Flow for Bayesian Inverse Problem
Sep 3, 2026Yang Zhao, Junxiong Jia, Tao ZhouBayesian Inverse Problems Normalizing Flows
School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China · Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, 100190, China
SafeDivertor: Faithful Divertor Heat Flux Reconstruction from Macroscopic Plasma State Signals via Time-Frequency Prior Exploitation
Aug 6, 2026Hao Si, Zehua Chen, Qingquan Yang +8Heat Diffusion Exploitation
School of Computer Science and Technology, Anhui University, Hefei 230601, China · Department of Computer Science and Technology, Tsinghua University, Beijing, China · Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230601, China +1
A Physics-Informed Neural Operator for Thermal Ranking of Low-Cost Wall Materials in Hot-Dry Climates
Jul 28, 2026Muhammad Akbar Khan, Fahim Raees, Ubaida FatimaHeat Diffusion Materials
Department of Mathematics, NED University of Engineering and Technology, Karachi 75270, Pakistan
A hybrid analytical-PINN model for subsurface simulation of geothermal heat exchangers in heterogeneous underground
Jul 14, 2026Moke Rao, Thomas Hamacher, Smajil HalilovicHeat Diffusion Parametric Physics-Informed Neural Network
Technical University of Munich, Chair of Renewable and Sustainable Energy Systems, Germany
Beyond Thermal Imaging: Inferring Thermophysical Properties from Time-Resolved Thermal Observations
Jul 8, 2026Chenghao Xu, Malcolm Mielle, Olga FinkThermal Imaging Heat Diffusion
Intelligent Maintenance and Operations Systems, ´Ecole polytechnique f´ed´erale de Lausanne, Station 18, Lausanne, 1015, Vaud, Switzerland. · Schindler Lab EPFL, Schindler Holding AG, Station 18, Lausanne, 1015, Vaud, Switzerland.
HPG-Diff: Hierarchical physics-guided diffusion with differentiable connectivity constraints for topology optimization
Jul 8, 2026Jinbo Yang, Mingyue Yuan, Boyuan Zhang +2Topology Optimization Physics-Guided Diffusion
School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China · Computer Science and Engineering, University of New South Wales, Sydney, 2052, Australia · College of Intelligence and Computing, Tianjin University, Tianjin, 300072, China +1
Temperature Field Reconstruction of Tungsten Monoblock Divertor on EAST using Physics-aware Neural Operator Transformer
Jun 30, 2026Zikang Yan, Xiao Wang, Qingquan Yang +6Heat Diffusion Neural Operators
School of Computer Science and Technology, Anhui University, Hefei, China · Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, China · Tongling University, Tongling 244000, China +2
Projection-based coupling of infrared thermography and stereocorrelation-based digital image correlation
Jun 27, 2026Jendrik-Alexander Tröger, Lutz Müller-Lohse, Stefan HartmannThermal Imaging Heat Diffusion
Institute of Applied Mechanics, Clausthal University of Technology, Adolph-Roemer-Straße 2a, 38678 Clausthal-Zellerfeld, Germany
Physics-Informed Modeling for Wood Thermal Analysis and Prediction
Jun 22, 2026Jingren Xie, Alex John Buckthal, Ryan Anthony O'Connor +2Heat Diffusion Physics-Informed Learning
Technical University of Denmark Denmark · Pioneer Centre for AI Denmark · The Royal Danish Academy Denmark
Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation
Jun 7, 2026Michael ChinUncertainty Quantification Neural Operators
Independent Researcher
Overcoming the Limits of Finite Difference Method; Physics-Informed Neural Network for Noisy High-Dimensional Heat Diffusion
Jun 6, 2026Shreesh Bhattarai, Harish Chandra BhandariHeat Diffusion Time Discretization
Department of Mathematics, Kathmandu University Dhulikhel, Nepal
Reconstructing Unobservable Temperature Fields via Simulation-Aided Intelligent Sensing
Jun 3, 2026Monika Stipsitz, Hèlios Sanchis-Alepuz, Jacob Reynvaan +1Rgb-Thermal Heat Diffusion
Embedded Systems Silicon Austria Labs GmbH Graz, Austria
NUCLEUS-MoE: Unified Model of Pool Boiling for Liquid Cooling
May 26, 2026Arthur Feeney, Xianwei Zou, Sheikh Md Shakeel Hassan +2Surrogate Models Molten Pool
Department of Electrical Engineering and Computer Science University of California, Irvine Irvine, CA, USA
Faster Thermal Profiling of a Lunar Rover with Machine Learning Adapted Finite Difference Model
May 26, 2026Samuel Weber, Zaki Hasnain, Souma ChowdhuryHeat Diffusion Rosetta
University at Buffalo · Department of Mechanical and Aerospace Engineering · Zij Sciences +1
Open Multimodal Datasets and Open-Source Software for Data-Driven Modeling of Multiphase Transport and Thermal Systems
May 21, 2026Christy Dunlap, Hari Pandey, Stephen Pierson +6Multimodal Dataset Data-Driven
Department of Mechanical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
In-context learning enables continental-scale subsurface temperature prediction from sparse local observations
May 15, 2026Daniel O'Malley, Christopher W. Johnson, Javier E. Santos +10Subsurface Scattering Land Surface Temperature
Los Alamos National Laboratory
A numerical study into neural network surrogate model performance for uncertainty propagation
May 15, 2026Noah Wade, Kirubel TeferraSurrogate Models Heat Diffusion
ASEE Postdoctoral Associate, U.S. Naval Research Laboratory, Washington, DC, 20375, USA · U.S. Naval Research Laboratory, Washington, 20375, DC, USA
Conditional Entropy of Heat Diffusion on Temporal Networks
May 15, 2026Samuel Koovely, Alexandre BovetChange-Point Detection Temporal Dynamics
Department of Mathematical Modeling and Machine Learning University of Zurich Zurich, Switzerland
Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning
May 7, 2026Umme Mahbuba Nabila, Paul Seurin, Linyu Lin +1Digital Twins Surrogate Models
Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109, United States · Nuclear Science & Technology Division, Idaho National Laboratory, Idaho Falls, ID 83415, United States · Department of Computer Science and Engineering, University of Michigan, Ann Arbor, MI 48109, United States
An adaptive wavelet-based PINN for problems with localized high-magnitude source
Apr 30, 2026Himanshu Pandey, Ratikanta BeheraParametric Physics-Informed Neural Network Heat Diffusion
Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560012, India
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
Apr 18, 2026Yixuan WangPartial Differential Equations Singularity
CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California · [math.NA]
Physics-Informed Machine Learning for Pouch Cell Temperature Estimation
Apr 16, 2026Zheng LiuHeat Diffusion Electric Vehicles
Department of Industrial and Manufacturing Systems Engineering University of Michigan-Dearborn Dearborn, USA
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks. Application to Insulation Material Degradation Prognostics
Jan 7, 2026Ibai Ramirez, Jokin Alcibar, Joel Pino +2Parametric Physics-Informed Neural Network Heat Diffusion
Department of Electronics and Computer Science Mondragon University Arrasate-Mondragon, 20500, Spain · CARTIF Technology Centre Valladolid, 47151, Spain · Department of Physical Chemistry University of the Basque Country (EHU)[cs.LG] Basque Centre for Applied Mathematics (BCAM) Leioa, 20018, Spain +1

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Learning PDE Dynamics between Submanifolds Using Green's Observation Operators

Jan Tauberschmidt, Jephte Abijuru, Samuel Okon, Naukshatro Bose+4

German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany · Rheinland-Pfälzische Technische Universität (RPTU), Kaiserslautern, Germany · University of Manchester, Manchester, United Kingdom

Heat Diffusion

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Many physical systems are driven and observed only on lower-dimensional submanifolds of a larger spatial domain, while their dynamics are governed by the ambient medium occupying that domain. Examples include laser-heated parts imaged by an infrared camera, and ground-level emissions measured on a sensor plane. Full-domain solvers, however, compute the entire volume for every new source although only the observation submanifold is needed, and black-box surrogates do not exploit that the ambient medium remains fixed. We introduce the \emph{Green's Observation Operator (GObO)}, which maps the ambient medium once to the Green's kernel of a linear PDE restricted to the source and observation submanifolds. New sources then cost one lower-dimensional integral and no network evaluation. Exponential rates in the kernel yield an exact finite streaming state with horizon-independent memory; we prove its stability and an approximation rate for the restricted heat kernel. On three-dimensional heat conduction and advection--diffusion with collocated and distinct source and observation geometries, GObO trained on static sources predicts responses to moving sources zero-shot with 4--8

\times

lower error than black-box surrogates, at 1.4,ms per query after a single conditioning pass. The same kernel transfers across resolutions and admits corrections for mild nonlinearities, including radiative losses and temperature-dependent conductivity, without retraining, at the cost of lower in-distribution accuracy.

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