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Adaptive reduced basis trust region methods for parabolic inverse problems
Michael Kartmann, Benedikt Klein, Mario Ohlberger, Thomas Schuster and Stefan Volkwein Inverse Problems 41(12) 125006 (2025) https://doi.org/10.1088/1361-6420/ae2a66
An Augmented Lagrangian Trust‐Region Method With Inexact Gradient Evaluations to Accelerate Constrained Optimization Problems Using Model Hyperreduction
Adaptive reduced basis trust region methods for parameter identification problems
Michael Kartmann, Tim Keil, Mario Ohlberger, Stefan Volkwein and Barbara Kaltenbacher Computational Science and Engineering 1(1) (2024) https://doi.org/10.1007/s44207-024-00002-z
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
A globally convergent method to accelerate large-scale optimization using on-the-fly model hyperreduction: Application to shape optimization
Adaptive machine learning-based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery
Tim Keil, Hendrik Kleikamp, Rolf J. Lorentzen, Micheal B. Oguntola and Mario Ohlberger Advances in Computational Mathematics 48(6) (2022) https://doi.org/10.1007/s10444-022-09981-z
Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation
Julian Andrej, Lars Grüne, Luca Mechelli, Thomas Meurer, Simon Pirkelmann and Stefan Volkwein Computers & Mathematics with Applications 116 71 (2022) https://doi.org/10.1016/j.camwa.2021.09.004
A Trust Region Reduced Basis Pascoletti-Serafini Algorithm for Multi-Objective PDE-Constrained Parameter Optimization
Stefan Banholzer, Luca Mechelli and Stefan Volkwein Mathematical and Computational Applications 27(3) 39 (2022) https://doi.org/10.3390/mca27030039