Operator Learning

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12 papers in the last four weeks, up 200% on the four weeks before. 0.1% of all new papers.

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  1. Deep Spectral Learning of Embedded Latent Transfer Operators for Stochastic Dynamical Systems

    Jun 12, 2026Ryogo Tanaka, Yoshinobu KawaharaDynamical SystemsStochastic Linear Dynamical Systems

    Graduate School of Information Science and Technology, The University of Osaka, Osaka, Japan · Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan

  2. Harness In-Context Operator Learning with Chain of Operators

    Jun 10, 2026Minghui Yang, Ling Guo, Liu YangOOD GeneralizationPDE Operator Learning

    Department of Mathematics, Shanghai Normal University, Shanghai, China · Department of Mathematics, National University of Singapore, Singapore

  3. Operator learning for the 2D incompressible Navier-Stokes equations: a conformal prediction approach in the data-scarce regime

    Jun 7, 2026Weinan Wang, Bowen Gang, Hao DengUncertainty QuantificationConformal Prediction

    Department of Mathematics, University of Oklahoma, Norman, OK, USA · Department of Statistics and Data Science, School of Management, Fudan University, Shanghai, China

  4. Spectral Audit of In-Context Operator Networks

    Jun 1, 2026Zhiwei Gao, Liu Yang, George Em KarniadakisPDE Operator LearningOperator Learning

    Division of Applied Mathematics, Brown University, Providence, RI, USA · Department of Mathematics, National University of Singapore, Singapore

  5. Variation Spaces for Encoder--Decoder Neural Operators: Approximation and Generalization

    May 31, 2026Jia-Qi Yang, Lei ShiNeural Network Approximation TheoryOperator Learning

    School of Mathematical Sciences and Shanghai Key Laboratory for Contemporary Applied Mathematics, Fudan University, Shanghai 200433, China.

  6. Is Zero-Shot Super-Resolution Possible in Operator Learning?

    May 29, 2026Unique Subedi, Ambuj TewariOperator LearningStatistical Learning Theory

    Department of Statistics, University of Michigan

  7. Functional Attention: From Pairwise Affinities to Functional Correspondences

    May 29, 2026Jiefang Xiao, Maolin Gao, Simon Weber +2PDE Operator LearningAttention Mechanisms

    Technical University of Munich, Germany · Munich Center for Machine Learning (MCML), Germany · PIXL, Department of Computer Science, University of Oxford, United Kingdom +1

  8. Measure-to-measure Regression with Transformers

    May 27, 2026Matthew Vandergrift, Martha White, Yury Polyanskiy +2TransformerOperator Learning

    University of Alberta · Canada CIFAR AI Chair · MIT +1

  9. High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention

    May 26, 2026Deepak Akhare, Mohammad Amin Nabian, Corey Adams +2Low-Rank AttentionSurrogate Modeling

    Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN · NVIDIA, San Jose, CA · General Motors, Detroit, MI

  10. Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach

    May 22, 2026Qian Zhang, George Em KarniadakisPDE Operator LearningOperator Learning

    Division of Applied Mathematics, Brown University

  11. Optimization of randomized neural networks for transfer operator approximation

    May 22, 2026Mohammad Tabish, Stefan KlusDynamical SystemsNeural Network Optimization

    Maxwell Institute for Mathematical Sciences, University of Edinburgh and Heriot–Watt University, Edinburgh, UK · School of Mathematical & Computer Sciences, Heriot–Watt University, Edinburgh, UK

  12. Multiple Neural Operators Achieve Near-Optimal Rates for Multi-Task Learning

    May 21, 2026Adrien Weihs, Hayden SchaefferNeural Network Approximation TheoryOperator Learning

    Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095, USA.

  13. Nonlocal operator learning for fMRI encoding and decoding tasks

    May 19, 2026Andreas Kramer, Saugat Acharya, Alice Giola +1Neural DecodingNeuroimaging

    Department of Computer Science, Idaho State University 921 S. 8th Ave Mail Stop 8060, Pocatello, ID 83209-8023 · Department of Mathematics and Statistics, Idaho State University Physical Science Complex, 921 S. 8th Ave., Stop 8085, Pocatello, ID 83209

  14. Smooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions

    May 19, 2026Ha Dang, Sebastian Schmidt, Juergen HesserPDE Operator LearningDeep Operator Networks

    Mannheim Institute for Intelligent Systems in Medicine, Heidelberg University · Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University · Heidelberg Institute for Theoretical Studies (HITS), Heidelberg University +2

  15. Function graph transformers universally approximate operators between function spaces

    May 18, 2026Takashi Furuya, David Mis, Ivan Dokmanić +2Transformer AttentionNeural Network Approximation Theory

    Doshisha University, RIKEN AIP · Rice University · University of Basel +2

  16. Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations

    May 16, 2026Phuoc-Toan Huynh, Richard Archibald, Feng BaoUncertainty QuantificationDeep Operator Networks

    Department of Mathematics, Florida State University, Tallahassee, FL, USA · Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

  17. Universal Approximation of Nonlinear Operators and Their Derivatives

    May 14, 2026Filippo de FeoNeural Network Approximation TheoryOperator Learning

    Institut für Mathematik, Technische Universität Berlin.

  18. Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing

    May 14, 2026Ellwil Sharma, Arastu SharmaSparse Mixture-of-ExpertsPDE Operator Learning

    Shodh AI

  19. UFO: A Domain-Unification-Free Operator Framework for Generalized Operator Learning

    May 12, 2026Hanli Qiao, George Em Karniadakis, Muhammad MuniruzzamanCross-Domain GeneralizationPDE Operator Learning

    Water and Mining Environment Unit, Geological Survey of Finland, Vuorimiehentie 5, Espoo, 02151, Finland · Division of Applied Mathematics, Brown University, 170 Hope Street, Providence, RI 02912, USA · Institute of Geosciences, University of Bonn, Kirschallee 1-3, Bonn, 53115, Germany

  20. Approximation of Maximally Monotone Operators : A Graph Convergence Perspective

    May 12, 2026Takashi Furuya, Yury Korolev, Takaharu YaguchiNeural Network Approximation TheoryOperator Learning

    Doshisha University, RIKEN AIP · Department of Mathematical Sciences, University of Bath, UK · Kyushu University, RIKEN AIP

  21. A Deep Risk Estimator for Known Operator Learning

    May 8, 2026Andreas Maier, Md Hasan, Paulina Conrad +1Neural Network GeneralizationNeural Network Approximation Theory

    Pattern Recognition Lab · Friedrich-Alexander-Universität Erlangen-Nürnberg · Erlangen, Germany

  22. Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators

    May 5, 2026Zachary Morrow, Joseph Crockett, John D. Jakeman +1Surrogate ModelingWildfire Forecasting

    Sandia National Laboratories 1515 Eubank Blvd SE, Albuquerque, NM 87123

  23. HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs

    May 1, 2026Jinpai Zhao, Nishant Panda, Yen Ting Lin +3Neural Surrogate ModelingNeural Network Interpretability

    Oden Institute University of Texas at Austin Austin, TX, USA · Information Sciences, CAI-3 Los Alamos National Laboratory Los Alamos, NM 87545, USA · Norwegian University of Life Sciences Ås, Norway / Simula Research Lab. Oslo, Norway

  24. Physics-Guided Dimension Reduction for Simulation-Free Operator Learning of Stiff Differential-Algebraic Systems

    Apr 21, 2026Huy Hoang Le, Haoguang Wang, Christian Moya +2Reduced-Order ModelingDeep Operator Networks

    School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 USA · Department of Mathematics, Purdue University, West Lafayette, IN 47907 USA · Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA

  25. Learning the Riccati solution operator for time-varying LQR via Deep Operator Networks

    Apr 20, 2026Jun Chen, Umberto Biccari, Junmin WangFeedback ControlDeep Operator Networks

  26. Neural Shape Operator Surrogates -- Expression Rate Bounds

    Apr 20, 2026Helmut Harbrecht, Christoph SchwabPDE Operator LearningNeural Network Approximation Theory

  27. Learning Affine-Equivariant Proximal Operators

    Apr 16, 2026Oriel Savir, Zhenghan Fang, Jeremias SulamEquivariant Neural NetworksOperator Learning

    Mathematical Institute for Data Science, Johns Hopkins University, Baltimore, MD 21218, USA

  28. A short tour of operator learning theory: Convergence rates, statistical limits, and open questions

    Feb 28, 2026Simone Brugiapaglia, Nicola Rares Franco, Nicholas H. NelsenOperator LearningStatistical Learning Theory

    Concordia University · Politecnico di Milano · Cornell University and The University of Texas at Austin

  29. Fluids You Can Trust: Property-Preserving Operator Learning for Incompressible Flows

    Feb 17, 2026Ramansh Sharma, Matthew Lowery, Houman Owhadi +1PDE Operator LearningOperator Learning

    Kahlert School of Computing University of Utah UT, USA · Department of Computing and Mathematical Sciences California Institute of Technology CA, USA

  30. Learned iterative networks: An operator learning perspective

    Dec 9, 2025Andreas Hauptmann, Ozan ÖktemImage ReconstructionComputational Imaging

    Research Unit of Mathematical Sciences, University of Oulu, Finland · Department of Computer Science, University College London, United Kingdom · Department of Mathematics, KTH - Royal Institute of Technology, Sweden