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Pawan Goyal, Benjamin Peherstorfer and Peter Benner SIAM Journal on Scientific Computing 46(3) A1879 (2024) https://doi.org/10.1137/23M1554308
Active Operator Inference for Learning Low-Dimensional Dynamical-System Models from Noisy Data
Wayne Isaac Tan Uy, Yuepeng Wang, Yuxiao Wen and Benjamin Peherstorfer SIAM Journal on Scientific Computing 45(4) A1462 (2023) https://doi.org/10.1137/21M1439729
A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs
Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler and Tizian Wenzel SIAM Journal on Scientific Computing 45(3) A1039 (2023) https://doi.org/10.1137/22M1493318
Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference
Nihar Sawant, Boris Kramer and Benjamin Peherstorfer Computer Methods in Applied Mechanics and Engineering 404 115836 (2023) https://doi.org/10.1016/j.cma.2022.115836
Nonintrusive Reduced-Order Models for Parametric Partial Differential Equations via Data-Driven Operator Inference
Shane A. McQuarrie, Parisa Khodabakhshi and Karen E. Willcox SIAM Journal on Scientific Computing 45(4) A1917 (2023) https://doi.org/10.1137/21M1452810
Operator inference with roll outs for learning reduced models from scarce and low-quality data
Bayesian operator inference for data-driven reduced-order modeling
Mengwu Guo, Shane A. McQuarrie and Karen E. Willcox Computer Methods in Applied Mechanics and Engineering 402 115336 (2022) https://doi.org/10.1016/j.cma.2022.115336
Operator Inference of Non-Markovian Terms for Learning Reduced Models from Partially Observed State Trajectories