Neural Surrogate Modeling

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Overview

Neural surrogate modeling replaces repeated calls to expensive simulators with learned approximations of physical fields, system dynamics, or quantities of interest, making tasks such as design search, control, and Bayesian inference more practical. Common approaches include neural operators for PDE solution maps, graph neural networks for meshes and networks, reduced-order latent models, and physics-informed or hybrid models that combine learned components with governing equations. Researchers also use multi-fidelity training, active learning, and probabilistic models to reduce data needs and estimate uncertainty. A central challenge is that good one-step or in-distribution accuracy does not guarantee stable long rollouts, reliable extrapolation, physical consistency, or improved downstream decisions; classical solvers remain important when stringent accuracy and verification are required.

Latest papers

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418 papers45 papers in the last four weeks, down 15% on the four weeks before. 0.3% of all new papers.

  1. Physical Sensitivity Kernels Can Emerge in Data-Driven Forward Models: Evidence From Surface-Wave Dispersion

    Apr 5, 2026Ziye Yu, Yuqi Cai, Xin LiuNeural Surrogate ModelingSeismology

    Institute of Geophysics, China Earthquake Administration, Beijing 100081, China · Laboratory of Seismology and Physics of Earth’s Interior, School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China · Institute of Advanced Technology, University of Science and Technology of China, Hefei 230088, China

  2. Real-Time Surrogate Modeling for Personalized Blood Flow Prediction and Hemodynamic Analysis

    Apr 3, 2026Sokratis J. Anagnostopoulos, George Rovas, Vasiliki Bikia +3Neural Surrogate ModelingClinical Prediction

    Laboratory of Hemodynamics and Cardiovascular Technology, EPFL, Lausanne, Switzerland · Stanford DBDS and HAI, Stanford University, Palo Alto, USA · Medical School, National and Kapodistrian University of Athens, Athens, Greece

  3. Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting

    Apr 3, 2026Valentin Mercier, Serge Gratton, Lapeyre Corentin +1Flood ForecastingNeural Surrogate Modeling

    Toulouse INP, IRIT, EPE UT · Université de Toulouse, INP, IRIT, Toulouse, France · IRIT, EPE UT, Toulouse INP +3

  4. Application of parametric Shallow Recurrent Decoder Network to magnetohydrodynamic flows in liquid metal blankets of fusion reactors

    Apr 2, 2026M. Lo Verso, C. Introini, E. Cervi +3MagnetohydrodynamicsComputational Fluid Dynamics

    Department of Energy, Politecnico di Milano, Milano, 20133, Italy · MATHEP Group, Dept. of Energy "Galileo Ferraris", Politecnico di Torino, Torino, Italy · Autodesk Research, 6 Agar Street, London UK +1

  5. Neural Network-Assisted Model Predictive Control for Implicit Balancing

    Apr 2, 2026Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens +1Model Predictive ControlData-Driven Control

    IDLab, Ghent University – imec, Ghent, Belgium · Faculty of Technology, Policy & Management, Delft University of Technology, Delft, The Netherlands · Beebop.ai, Belgium

  6. Bias Inheritance in Neural-Symbolic Discovery of Constitutive Closures Under Function-Class Mismatch

    Apr 1, 2026Hanbing Liang, Ze Tao, Fujun LiuReaction-Diffusion SystemsPDE Discovery

    Nanophotonics and Biophotonics Key Laboratory of Jilin Province, School of Physics, Changchun University of Science and Technology, Changchun 130022, P.R. China

  7. Deep Learning-Accelerated Surrogate Optimization for High-Dimensional Well Control in Stress-Sensitive Reservoirs

    Apr 1, 2026Mahammad Valiyev, Jodel Cornelio, Behnam JafarpourSurrogate-Assisted OptimizationOptimal Control

    University of Southern California

  8. Real-Time Surrogate Modeling for Fast Transient Prediction in Inverter-Based Microgrids Using CNN and LightGBM

    Mar 31, 2026Osasumwen Cedric Ogiesoba-Eguakun, Kaveh Ashenayi, Suman RathPower SystemsNeural Surrogate Modeling

    Department of Electrical and Computer Engineering, The University of Tulsa, Tulsa, OK 74104, USA

  9. Derived Fields Increase the Recoverable Information in Budgeted Neural PDE Surrogate

    Mar 31, 2026Wenshuo Wang, Fan ZhangPDE Surrogate ModelingNeural Surrogate Modeling

    School of Future Technology, South China University of Technology, China · State Key Laboratory of Ocean Sensing & Ocean College, Zhejiang University, China · Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, USA

  10. Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks

    Mar 31, 2026Anci Lin, Zhiwen Zhang, Wenju ZhaoPhysics-Informed MLNeural Surrogate Modeling

    School of Mathematics, Shandong University, Jinan, Shandong, 250100, P.R. China. · Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong SAR, P.R. China. · Materials Innovation Institute for Life Sciences and Energy (MILES), HKU-SIRI, Shenzhen, P.R. China.

  11. Data-informed lifting line theory

    Mar 30, 2026Arjun Sharma, Jonas A. Actor, Peter A. BoslerComputational Fluid DynamicsNeural Surrogate Modeling

    Center for Computing Research, Sandia National Laboratories, Albuquerque, NM, 87185, USA

  12. Neural Approximation of Generalized Voronoi Diagrams

    Mar 27, 2026Panagiotis Rigas, George Ioannakis, Ioannis EmirisNeural Surrogate ModelingImplicit Neural Representations

    Department of Informatics & Telecommunications, National and Kapodistrian University of Athens, Greece · Archimedes, Athena Research Center, Greece · Institute for Language and Speech Processing, Athena Research Center, Greece

  13. Physics-Informed Neural Networks and Sequence Encoder: Application to heating and early cooling of thermo-stamping process

    Mar 27, 2026Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot +2Physics-Informed MLNeural Surrogate Modeling

    Nantes Université, Ecole Centrale Nantes, CNRS, GeM, UMR 6183, Nantes, 44321, France · Nantes Université, IRT Jules Verne, Bouguenais, 44340, France

  14. Toward Actionable Digital Twins for Radiation-Based Imaging and Therapy: Mathematical Formulation, Modular Workflow, and an OpenKBP-Based Dose-Surrogate Prototype

    Mar 26, 2026Hsin-Hsiung Huang, Bulent SoykanRadiotherapy Dose PredictionDigital Twins

    School of Data, Mathematical, and Statistical Sciences, University of Central Florida, Orlando, FL 32816 USA · Institute for Simulation and Training, University of Central Florida, Orlando, FL 32826 USA

  15. Anchored-Branched Steady-state WInd Flow Transformer (AB-SWIFT): a metamodel for 3D atmospheric flow in urban environments

    Mar 26, 2026Armand de Villeroché, Rem-Sophia Mouradi, Vincent Le Guen +5Neural Surrogate ModelingPDE Surrogate Modeling

    CEREA, ENPC, EDF R&D, Institut Polytechnique de Paris, Île-de-France, France · EDF R&D, Île-de-France, France · SINCLAIR AI Laboratory, Saclay, Île-de-France, France +1

  16. Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks

    Mar 25, 2026Easton Huch, Michael KeaneNeural Surrogate ModelingAmortized Inference

    Postdoctoral Fellow, Johns Hopkins Carey Business School · Carey Distinguished Professor, Johns Hopkins Carey Business School

  17. Learning Response-Statistic Shifts and Parametric Roll Episodes from Wave--Vessel Time Series via LSTM Functional Models

    Mar 25, 2026Jose del Aguila FerrandisNeural Surrogate Modeling

    Kevin T. Crofton Department of Aerospace and Ocean Engineering, Virginia Tech, USA

  18. SM-Net: Learning a Continuous Spectral Manifold from Multiple Stellar Libraries

    Mar 25, 2026Omar Anwar, Aaron S. G. Robotham, Luca Cortese +1AstrophysicsNeural Surrogate Modeling

    International Centre for Radio Astronomy Research (ICRAR) The University of Western Australia (UWA), 35 Stirling Hwy, Crawley WA 6009, Australia

  19. An Invariant Compiler for Neural ODEs in AI-Accelerated Scientific Simulation

    Mar 25, 2026Fangzhou Yu, Yiqi Su, Ray Lee +2Structure-Preserving Neural NetworksNeural ODEs

    Virginia Tech, VA, USA

  20. Biophysics-Enhanced Neural Representations for Patient-Specific Respiratory Motion Modeling

    Mar 23, 2026Jan Boysen, Hristina Uzunova, Heinz Handels +1Neural Surrogate ModelingMedical Image Analysis

    German Research Center for Artificial Intelligence (DFKI), Lübeck, DE · Clinic for Orthopedics and Orthopedic Surgery, University Medicine Greifswald, Greifswald, DE · Institute of Medical Informatics, University of Lübeck, Lübeck, DE

  21. BOOST-RPF: Boosted Sequential Trees for Radial Power Flow

    Mar 23, 2026Ehimare Okoyomon, Christoph GoebelPower SystemsSurrogate Modeling

    Professorship of Energy Management Technologies at the Technical University of Munich

  22. A Variational Latent-Space Framework for Uncertainty-Aware Spectral Image Emulation

    Mar 23, 2026Chedly Ben Azizi, Claire Guilloteau, Gilles Roussel +1Neural Surrogate ModelingVariational Autoencoders

    Univ. Littoral Côte d’Opale, LISIC – UR 4491, 62219, Longuenesse, France

  23. Direct Interval Propagation Methods using Neural-Network Surrogates for Uncertainty Quantification in Physical Systems Surrogate Model

    Mar 22, 2026Ghifari Adam Faza, Jolan Wauters, Fabio Cuzzolin +2Uncertainty PropagationUncertainty Quantification

    LMSD, Department of Mechanical Engineering, KU Leuven, Heverlee, 3001, Belgium · RAM, Department of Mechanical Engineering, KU Leuven, Brugge, 8200, Belgium · Visual Artificial Intelligence Laboratory, Oxford Brookes University, Oxford, UK +1

  24. Joint Surrogate Learning of Objectives, Constraints, and Sensitivities for Efficient Multi-objective Optimization of Neural Dynamical Systems

    Mar 22, 2026Frithjof Gressmann, Ivan Georgiev Raikov, Seung Hyun Kim +3Neural Surrogate ModelingSurrogate-Assisted Optimization

    Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign, Urbana, IL · The Grainer College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL · Department of Neurosurgery, Stanford University, Stanford, CA +3

  25. SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators

    Mar 20, 2026Mahmoud Elhadidy, Roshan M. D'Souza, Amirhossein ArzaniContinual LearningFourier Neural Operator

    Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA · Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA · Department of Mechanical Engineering, University of Wisconsin–Milwaukee, Milwaukee, WI, USA +1

  26. Enactor: From Traffic Simulators to Surrogate World Models

    Mar 18, 2026Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1Interactive World ModelsNeural Surrogate Modeling

    Department of CISE, University of Florida

  27. Gradient-Informed Temporal Sampling Improves Rollout Accuracy in PDE Surrogate Training

    Mar 18, 2026Wenshuo Wang, Fan ZhangTraining Data SelectionAdaptive Sampling

    School of Future Technology, South China University of Technology, China · State Key Laboratory of Ocean Sensing & Ocean College, Zhejiang University, China · Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, USA

  28. A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials

    Mar 18, 2026Purna Vindhya Kota, Meer Mehran Rashid, Somdatta Goswami +1Neural Surrogate ModelingHyperelasticity

    Department of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles Street, Baltimore, 21218, MD, USA

  29. RHYME-XT: A Neural Operator for Spatiotemporal Control Systems

    Mar 18, 2026Marijn Ruiter, Miguel Aguiar, Jake Rap +2PDE Surrogate ModelingPDE Operator Learning

    Digital Futures and Division of Decision and Control Systems, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden. · Control Systems Group, EE Dept., Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands

  30. Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation

    Mar 18, 2026Petros Ellinas, Indrajit Chaudhuri, Johanna Vorwerk +1Surrogate ModelingPower Systems

    Department of Wind and Energy Systems, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark.