Multifidelity Modeling

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3 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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  1. Adaptive hybrid coupling with operator inference, the overlapping Schwarz alternating method and reinforcement learning

    Sep 15, 2026Trishit Mondal, Irina Tezaur, Anthony GruberReinforcement LearningPDE Surrogate Modeling

    Worcester Polytechnic Institute

  2. Toward Reliable Railway-Bogie Response Prediction Using Multifidelity TDNN and Physics-Informed Residual Learning

    Sep 10, 2026Gyeolhee Lee, Moosun Kim, Taewook Kwon +3Surrogate ModelingResidual Learning

    Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea · Korea Railroad Research Institute, 176 Cheoldobangmulgwan-ro, Uiwang-si, Gyeonggi-do 16105, Republic of Korea · Department of Future Mobility, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea

  3. Selective boundary condition reduction via learned error gating

    Sep 8, 2026Daniel Fernández, Dominik Penk, Dominik RiedelbauchPDE Surrogate ModelingMultifidelity Modeling

    Chair for Dynamics, Control, Machine Learning, and Numerics (Alexander von Humboldt Professorship), Department of Mathematics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstraße, 91058 Erlangen, Germany. · Schaeffler Technologies AG & Co. KG, Industriestraße 1–3, Herzogenaurach, Germany.

  4. Out-Of-The-Loop Multi-Fidelity Bayesian Optimization

    Aug 4, 2026Gustavo Sutter, Hao Wang, Luis Ricardez-Sandoval +2Multi-Fidelity OptimizationBayesian Optimization

    Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada · Vector Institute, Toronto, ON, Canada · Department of Chemical Engineering, University of Waterloo, Waterloo, ON, Canada +2

  5. Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

    Jul 26, 2026Jaewook Lee, Ethan Errington, Christian D. Lorenz +1Multi-Fidelity OptimizationSurrogate Modeling

    Department of Engineering, King’s College London, London, WC2R 2LS, United Kingdom.

  6. Deep Gaussian Processes on Directed Acyclic Graphs

    Jul 10, 2026Federico L. Perlino, Oliver Hamelijnck, Adam M. Johansen +1Surrogate ModelingMultifidelity Modeling

    Department of Statistics, University of Warwick · 2AI Team, Unilink Software Ltd · Department of Computer Science, University of Warwick

  7. Compressing the Validation Bottleneck: An Agentic Self-Driving Lab for Scientific Discovery

    Jul 5, 2026Kyunghoon Hur, Chihun LeeAI for ScienceMultifidelity Modeling

    AX Research Division, Korea Electronics Technology Institute, Republic of Korea · Material Data Division, Korea Institute of Materials Science, Republic of Korea

  8. Multi-Fidelity SINDy: Sparse Discovery of Nonlinear Dynamical Systems with Fidelity-Weighted Measurements

    Jun 14, 2026Filippo Zacchei, Ana Larrañaga, Attilio Frangi +2Sparse Identification of Nonlinear DynamicsNonlinear System Identification

    MOX – Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy · Department of Mechanical Engineering, University of Washington, Seattle, Washington 98195, United States · Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy

  9. Bridged SBI: Correcting Biased Low-Fidelity Posteriors for Cost-Efficient High-Fidelity Inference

    Jun 8, 2026Gahee Kim, Yuki Kadokawa, Sandro M. Alcantara Tacora +5Simulation-Based InferenceRobotics Simulation

    NARA INSTITUTE OF SCIENCE AND TECHNOLOGY, Nara, Japan · PUBLIC WORKS RESEARCH INSTITUTE, Ibaraki, Japan

  10. Improvise, Adapt, Overcome: An On-The-Fly Multifidelity Algorithm for Efficient Machine Learning

    Jun 1, 2026Vivin Vinod, Peter ZaspelQuantum ChemistryMultifidelity Modeling

    School of Mathematics and Natural Sciences, University of Wuppertal, Germany.

  11. Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows

    May 27, 2026Jice Zeng, Shady E. Ahmed, David Barajas-Solano +1Uncertainty QuantificationMultifidelity Modeling

    Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, Richland, 99352, WA, USA

  12. Multi-Fidelity Learning with Shallow Recurrent Decoders for Reactor Physics

    May 22, 2026Stefano Riva, Carolina Introini, J. Nathan Kutz +1Neural Surrogate ModelingRecurrent Neural Networks

    Autodesk Research, London, UK · Department of Energy, Nuclear Engineering Division, Politecnico di Milano, Milan, Italy · Department of Mechanical and Nuclear Engineering and Emirates Nuclear Technology Center, Khalifa University, Abu Dhabi (127788), United Arab Emirates

  13. Multi-Fidelity Flow Matching: Cascaded Refinement of PDE Solutions

    May 15, 2026Sipeng Chen, Junliang Liu, Hewei Tang +1Surrogate ModelingConditional Flow Matching

    Department of Computer Science, Florida State University · Department of Materials Science and Engineering, Florida State University · Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin

  14. Multifidelity Gaussian process regression for solving nonlinear partial differential equations

    May 11, 2026Fatima-Zahrae El-Boukkouri, Josselin Garnier, Olivier RoustantSurrogate ModelingPDE Solving

    Institut de Mathématiques de Toulouse, Université de Toulouse, INSA, Toulouse, 31077, France · CMAP, CNRS, Ecole polytechnique, Institut Polytechnique de Paris, Palaiseau, 91120, France

  15. Hierarchical Multi-Fidelity Learning for Predicting Three-Dimensional Flame Wrinkling and Turbulent Burning Velocity

    May 6, 2026Saghar Zolfaghari, Yu Xie, Junfeng Yang +1Neural Surrogate ModelingMultifidelity Modeling

    Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA · School of Mechanical Engineering, University of Leeds, Leeds, UK

  16. Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks

    May 4, 2026Haizhou Wen, Elham Kiyani, Gang Li +3Surrogate ModelingSurrogate-Assisted Optimization

    Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA · Division of Applied Mathematics, Brown University, Providence, RI 02912, USA · Center for Composite Materials, University of Delaware, Newark, DL 19716, USA +4

  17. Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations

    Apr 28, 2026Gabriel de Miranda Nascimento, Marc L. Descoteaux, Laura Zichi +9Machine Learning Interatomic PotentialsMultifidelity Modeling

    Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA · John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA · Robert Bosch LLC Research and Technology Center, Watertown, MA, USA

  18. Adaptive multi-fidelity optimization with fast learning rates

    Apr 17, 2026Come Fiegel, Victor Gabillon, Michal ValkoMulti-Fidelity OptimizationBlack-Box Optimization

    ´Ecole Normale Sup´erieure, Paris · Huawei R&D, UK · Inria Lille

  19. Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data

    Mar 23, 2026Atticus Rex, Elizabeth Qian, David PetersonSurrogate ModelingMultifidelity Modeling

    School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA · School of Computational Science & Engineering, Georgia Institute of Technology, Atlanta, GA · Air Force Research Lab, Wright-Patterson AFB, Dayton, Ohio

  20. Optimization-Embedded Active Multi-Fidelity Surrogate Learning for Multi-Condition Airfoil Shape Optimization

    Mar 17, 2026Isaac Robledo, Alberto Vilariño, Arnau Miró +3Multi-Fidelity OptimizationSurrogate Modeling

    Aerial Platforms Department Subdirectorate General for Aeronautical Systems Spanish National Institute for Aerospace Technology (INTA) · Department of Aerospace Engineering Universidad Carlos III de Madrid Madrid, Spain · TUAREG Research Group Universitat Politècnica de Catalunya (UPC) CASE Large-Scale Computational Fluid Dynamics Barcelona Supercomputing Centre (BSC) Barcelona, Spain

  21. Bifidelity Parameter Estimation Using Conditional Diffusion Models

    Apr 2, 2025Caroline Tatsuoka, Minglei Yang, Dongbin Xiu +1Simulation-Based InferenceSurrogate Modeling

    Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA · Fusion Energy Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA · Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA