Reduced-Order Modeling

Ask about this topic

Overview

Reduced-order modeling represents a high-dimensional system with a smaller set of variables so it can be simulated or controlled at lower computational cost. Common approaches include proper orthogonal decomposition and Galerkin projection, dynamic mode decomposition, balanced truncation, and operator inference; newer methods use autoencoders, neural operators, and learned latent dynamics. Researchers increasingly combine these tools with physical constraints, adaptive basis updates, data assimilation, and uncertainty estimates, across applications such as fluid flow, materials, combustion, and robotics. A central challenge is balancing compact representations and fast predictions against stability, accuracy over long time horizons, and reliable generalization to new conditions.

Latest papers

CardsList

97 papers10 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. A Unified Framework for Structured Flow Modeling: From Representation to Verification and Model Discovery

    May 18, 2026Diego CasadeiDynamical SystemsHodge Decomposition

    Fly High Engineering AG, Badenerstrasse 13, 5200 Brugg AG, Switzerland

  2. pyforce-1.0.0: Python Framework for data-driven model Order Reduction of multi-physiCs problEms

    May 18, 2026Stefano Riva, Yantao Luo, Carolina Introini +1Multiphysics SimulationReduced-Order Modeling

    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

  3. Physics-Informed Reduced-Order Operator Learning for Hyperelasticity in Continuum Micromechanics

    May 8, 2026Hamidreza Eivazi, Henning WesselsStructural MechanicsHyperelasticity

    Division Data-Driven Modeling of Mechanical Systems, Institute of Applied Mechanics, Technische Universität Braunschweig, Pockelsstr. 3, 38106 Braunschweig, Germany

  4. PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN

    May 8, 2026Yixiong Jing, Xingyuan Chen, Guangming Wang +3Graph Neural NetworksRobotics Simulation

    University of Cambridge · Shanghai Jiao Tong University

  5. Discrete Elastic Ribbons: A Unified Discrete Differential Geometry Framework for One-Dimensional Energy Models

    May 7, 2026Shivam Kumar Panda, M Khalid JawedStructural MechanicsReduced-Order Modeling

    University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, 90095, CA, United States of America

  6. Reduced-order Neural Modeling with Differentiable Simulation for High-Detail Tactile Perception

    May 6, 2026Yuhu Guo, Zhikai Shen, Jiasheng Qu +4Neural Surrogate ModelingMaterial Point Method

    The University of Manchester, UK · The Chinese University of Hong Kong, Hong Kong SAR, China · University of Leeds, UK +1

  7. Constrained Extreme Gradient Boosting for Parametric Proper Orthogonal Decomposition Subspace Prediction

    May 5, 2026Melika Baghi, Xiao Liu, Kamran PaynabarGradient-Boosted Decision TreesReduced-Order Modeling

    Georgia Institute of Technology, Atlanta, GA 30332, USA

  8. Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction

    May 5, 2026Henning Schwarz, Pyei Phyo Lin, Jens-Peter M. Zemke +1Neural Surrogate ModelingImplicit Neural Representations

    Institute for Fluid Dynamics and Ship Theory, Hamburg University of Technology, Am Schwarzenberg-Campus 4, D-21073 Hamburg, Germany · Institute of Mathematics, Hamburg University of Technology, Am Schwarzenberg-Campus 3, D-21073 Hamburg, Germany

  9. Data-Driven Hamiltonian Reduction for Superconducting Qubits via Meta-Learning

    Apr 27, 2026Arielle Sanford, Andrew T. Kamen, Frederic T. Chong +1Reduced-Order ModelingData-Efficient Learning

    Department of Computer Science, University of Chicago, Chicago, IL 60637 · Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL 60637 · Johns Hopkins Applied Physics Laboratory, Laurel, MD 20723

  10. Conditional Score-Based Modeling of Effective Langevin Dynamics

    Apr 27, 2026Ludovico T. GiorginiLangevin DynamicsModel Calibration

    Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

  11. Machine learning moment closure models for the radiative transfer equation IV: enforcing symmetrizable hyperbolicity in two dimensions

    Apr 22, 2026Juntao HuangReduced-Order ModelingScientific ML

    Department of Mathematical Sciences, University of Delaware, Newark, DE, 19716, USA.

  12. 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

  13. HALO: Hybrid Auto-encoded Locomotion with Learned Latent Dynamics, Poincaré Maps, and Regions of Attraction

    Apr 20, 2026Blake Werner, Sergio A. Esteban, Massimiliano De Sa +2Dynamical SystemsHumanoid Robot Locomotion

    Caltech, Pasadena, CA, USA · NC State University, Raleigh, NC, USA

  14. Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems

    Apr 13, 2026Ananda Chakrabarti, Haitham H. Saleh, Indranil Nayak +3Reduced-Order ModelingDynamic Mode Decomposition

    Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA · ElectroScience Laboratory, The Ohio State University, Columbus, OH 43212, USA · SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025, USA +1

  15. AE-ViT: Stable Long-Horizon Parametric Partial Differential Equations Modeling

    Apr 7, 2026Iva Mikuš, Boris Muha, Domagoj VlahPDE Surrogate ModelingReduced-Order Modeling

    University of Zagreb Faculty of Electrical Engineering and Computer Science · University of Zagreb Faculty of Science Department of Mathematics

  16. Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic with an adaptive reduced-order model

    Apr 5, 2026Zesheng Yao, Zhen-Hua Wan, Canjun Yang +2Sample-Efficient RLModel-Based RL

    School of Mechanical Engineering, Zhejiang University, Hangzhou, PR China · Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, 117575 Singapore · Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China

  17. A Dynamic Toolkit for Transmission Characteristics of Precision Reducers with Explicit Contact Geometry

    Apr 2, 2026Jiacheng Miao, Chao Liu, Qiliang Wang +2Dynamical SystemsMultibody Dynamics

    Intelligent Equipment Division, CRRC Qishuyan Institute Co., Ltd, Changzhou, 213011, China · School of Mechanical Engineering, Dalian Jiaotong University, Dalian, 116028, China · Research Institute, CRRC Qishuyan Institute Co., Ltd, Changzhou, 213011, China

  18. A graph neural network based chemical mechanism reduction method for combustion applications

    Mar 20, 2026Manuru Nithin Padiyar, Priyabrat Dash, Konduri AdityaReduced-Order ModelingGraph Neural Networks

    Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, 560012, KA, India

  19. Generalized Task-Driven Design of Soft Robots via Reduced-Order FEM-based Surrogate Modeling

    Mar 20, 2026Yao Yao, David Howard, Perla MaiolinoSoft RoboticsSurrogate Modeling

    Oxford Robotics Institute, University of Oxford, UK · CSIRO Robotics, CSIRO, Australia

  20. Model Order Reduction of Cerebrovascular Hemodynamics Using POD_Galerkin and Reservoir Computing_based Approach

    Mar 19, 2026Rahul Halder, Arash Hajisharifi, Kabir Bakhshaei +1Reduced-Order ModelingPDE Surrogate Modeling

    Mathematics Area, mathLab, SISSA, via Bonomea 265, I-34136 Trieste, Italy · Biorobotics Institute, SMART Lab, Sant’Anna School of Advanced Studies, Pisa, Italy · Department of Computer Science, University of Pisa, Pisa, Italy

  21. End-to-end data-driven prediction of urban airflow and pollutant dispersion

    Mar 18, 2026Nishant Kumar, Franck Kerhervé, Lionel Agostini +1Air Quality PredictionSpatiotemporal Forecasting

    Institut Pprime, CNRS, Université de Poitiers, ISAE-ENSMA, Curiosity Team, Bât. H2 - Bd. Marie & Pierre Curie TSA 51124, 86073 Poitiers Cedex 9, France

  22. Data-driven model order reduction for structures with piecewise linear nonlinearity using dynamic mode decomposition

    Mar 18, 2026Akira Saito, Masato TanakaReduced-Order ModelingDynamical Systems

    Department of Mechanical Engineering, Meiji University, Kawasaki, Kanagawa 214-8571, Japan. · Toyota Research Institute of North America Toyota Motor North America, Inc. Ann Arbor, Michigan, 48105, USA

  23. Trajectory-Optimized Time Reparameterization for Learning-Compatible Reduced-Order Modeling of Stiff Dynamical Systems

    Mar 17, 2026Joe Standridge, Daniel Livescu, Paul CizmasReduced-Order ModelingDynamical Systems

    Texas A&M University, College Station, Texas 77840 · Los Alamos National Laboratory, Los Alamos, New Mexico 87545

  24. A convolutional autoencoder and neural ODE surrogate modeling framework applied to transient counterflow flames

    Mar 16, 2026Mert Yakup Baykan, Weitao Liu, Mohammad Rafi Malik +4AutoencodersPDE Surrogate Modeling

    Department of Aerospace Engineering, KAIST, Daejeon, Republic of Korea · Clean Energy Research Platform (CERP), KAUST, Thuwal, Saudi Arabia · Institute for Reactive Flows (IRST), University of Stuttgart, Pfaffenwaldring 31, 70569 Stuttgart, Germany

  25. Deep Invertible Autoencoders for Dimensionality Reduction of Dynamical Systems

    Mar 13, 2026Nicolò Botteghi, Silke Glas, Christoph BruneAutoencodersPDE Surrogate Modeling

    1MOX Laboratory, Department of Mathematics, Politecnico di Milano, Milano, Italy · Department of Applied Mathematics, University of Twente, Enschede, Netherlands

  26. Surrogates for Physics-based and Data-driven Modelling of Parametric Systems: Review and New Perspectives

    Mar 13, 2026Matteo Giacomini, Pedro DíezSurrogate ModelingReduced-Order Modeling

    Laboratori de Càlcul Numeric (LaCàN), E.T.S. de Ingeniería de Caminos, Canales y Puertos, Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain. · Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Barcelona, Spain.

  27. Push, Press, Slide: Mode-Aware Planar Contact Manipulation via Reduced-Order Models

    Mar 12, 2026Melih Özcan, Umut Orguner, Ozgur S. OguzNon-Prehensile Robotic ManipulationRobotic Manipulation

    Dept. of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkiye. · Dept. of Computer Engineering, Bilkent University, Ankara, Turkiye.

  28. Surrogate models for nuclear fusion with parametric Shallow Recurrent Decoder Networks: applications to magnetohydrodynamics

    Mar 11, 2026M. Lo Verso, C. Introini, E. Cervi +3MagnetohydrodynamicsNeural Surrogate Modeling

    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

  29. NN-OpInf: an operator inference approach using structure-preserving composable neural networks

    Mar 9, 2026Eric Parish, Anthony Gruber, Patrick Blonigan +1Structure-Preserving Neural NetworksReduced-Order Modeling

    Sandia National Laboratories, Livermore, CA, USA · Sandia National Laboratories, Albuquerque, NM, USA

  30. On Geometry Regularization in Autoencoder Reduced-Order Models with Latent Neural ODE Dynamics

    Mar 3, 2026Mikhail OsipovReduced-Order ModelingAutoencoders

    Independent Researcher, Italy