A non-conforming dual approach for adaptive Trust-Region Reduced Basis approximation of PDE-constrained optimization. - Tim Keil; Luca Mechelli; Mario Ohlberger; Felix Schindler; Stefan Volkwein (CoRR, 2020)

An adaptive projected Newton non-conforming dual approach for trust-region reduced basis approximation of PDE-constrained parameter optimization. - Stefan Banholzer; Tim Keil; Luca Mechelli; Mario Ohlberger; Felix Schindler; Stefan Volkwein (CoRR, 2020)

Numerical Upscaling of Perturbed Diffusion Problems. - Fredrik Hellman; Tim Keil; Axel Målqvist (SIAM J. Sci. Comput., 2020)

Model Reduction for Large Scale Systems. - Tim Keil; Mario Ohlberger (LSSC, 2021)

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; Mario Ohlberger (Adv. Comput. Math., 2022)

A relaxed localized trust-region reduced basis approach for optimization of multiscale problems. - Tim Keil; Mario Ohlberger (CoRR, 2022)

Adaptive Reduced Basis Methods for Multiscale Problems and Large-scale PDE-constrained Optimization. - Tim Keil (CoRR, 2022)

Adaptive Localized Reduced Basis Methods for Large Scale PDE-Constrained Optimization. - Tim Keil; Mario Ohlberger; Felix Schindler (LSSC, 2023)

Adaptive Localized Reduced Basis Methods for Large Scale Parameterized Systems. - Tim Keil; Mario Ohlberger; Felix Schindler (CoRR, 2023)

Adaptive Reduced Basis Trust Region Methods for Parameter Identification Problems. - Michael Kartmann; Tim Keil; Mario Ohlberger; Stefan Volkwein; Barbara Kaltenbacher (CoRR, 2023)

An Online Efficient Two-Scale Reduced Basis Approach for the Localized Orthogonal Decomposition. - Tim Keil; Stephan Rave (SIAM J. Sci. Comput., 2023)

Local training and enrichment based on a residual localization strategy. - Tim Keil; Mario Ohlberger; Felix Schindler; Julia Schleuß (CoRR, 2024)

A super-localized generalized finite element method. - Philip Freese; Moritz Hauck; Tim Keil; Daniel Peterseim (Numerische Mathematik, 2024)