Research Interests | Nonlinear model order reduction for transport-dominated problems Reduced basis methods and linear model order reduction Scientific machine learning (neural networks, kernel methods) (Optimal) Control of dynamical systems |
Current Talks | • Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems. Minisymposium on "New Trends in Model Order Reduction and Learning" at ALGORITMY 2024, Central-European Conference on Scientific Computing, Podbanske Slides Link to event • Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems. YMMOR - Young Mathematicians in Model Order Reduction, Stuttgart Slides Link to event • Be greedy and learn - efficient and certified algorithms for parametrized optimal control problems. Oberseminar Numerik, Münster Slides Link to event • A new Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs. Minisymposium on "Adaptive Methods for Surrogate and Reduced Order Modeling" at ADMOS (XI International Conference on Adaptive Modeling and Simulation), Göteborg Slides Link to event • Nonlinear model order reduction for parametrized transport-dominated PDEs using registration-based methods. YMMOR - Young Mathematicians in Model Order Reduction, Ulm Slides Link to event • Model order reduction with artificial neural networks in pyMOR. Minitutorial on "pyMOR - Model Order Reduction with Python" at SIAM CSE (SIAM Conference on Computational Science and Engineering) 2023, Amsterdam Slides Link to event • Nonlinear model order reduction for hyperbolic conservation laws by means of diffeomorphic transformations of space-time domains. Model Reduction and Surrogate Modeling (MORE), Berlin Slides Link to event • Nonlinear model order reduction for parametrized hyperbolic conservation laws in a space-time domain. Minisymposium on “Numerical methods for wave propagation problems” at CMAM (Computational Methods in Applied Mathematics) 2022, Wien Slides Link to event • Model order reduction using artificial neural networks. pyMOR School 2022, Magdeburg (online) Slides Link to event |
Current Publications | • Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling. Large-Scale Scientific ComputationsLecture Notes in Computer Science, 2024 online • Schembera, Björn; Wübbeling, Frank; Kleikamp, Hendrik; Biedinger, Christine; Fiedler, Jochen; Reidelbach, Marco; Shehu, Aurela; Schmidt, Burkhard; Koprucki, Thomas; Iglezakis, Dorothea; Göddeke, Dominik Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines. Metadata and Semantic Research - 17th Research Conference, MTSR 2023, Milan, Italy, October 25–27, 2023, Revised Selected PapersCommunications in Computer and Information Science, 2024 online • Kleikamp, Hendrik Application of an adaptive model hierarchy to parametrized optimal control problems. Proceedings of the Conference Algoritmy Vol. 2024, 2024 online • Kleikamp, Hendrik; Renelt, Lukas Two-stage model reduction approaches for the efficient and certified solution of parametrized optimal control problems. , 2024 online • Haasdonk B, Kleikamp H, Ohlberger M, Schindler F, Wenzel T A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs. SIAM Journal on Scientific Computing Vol. 45 (3), 2023 online • Kleikamp, Hendrik; Lazar, Martin; Molinari, Cesare Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems. , 2023 online • Kleikamp Hendrik, Ohlberger Mario, Rave Stephan Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain. MATHMOD 2022 - Discussion Contribution VolumeARGESIM ReportArXiv Vol. 17, 2022 online • Keil T, Kleikamp H, Lorentzen R, Oguntola M, Ohlberger M Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery. Advances in Computational Mathematics Vol. 2022 (48), 2022 online | hendrik dot kleikamp at uni-muenster dot de |
Phone | +49 251 83-35060 |
FAX | +49 251 83-32729 |
Room | 120.007 |
Secretary | Sekretariat Wernke Frau Silvia Wernke Telefon +49 251 83-35052 Fax +49 251 83-32729 Zimmer 120.001 |
Address | Herr Hendrik Kleikamp Angewandte Mathematik Münster: Institut für Analysis und Numerik Fachbereich Mathematik und Informatik der Universität Münster Orléans-Ring 10 48149 Münster |
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