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Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario., , , , , , , , , and 1 other author(s). CoRR, (2018)Greedy Kernel Methods for Accelerating Implicit Integrators for Parametric ODEs, , and . Numerical Mathematics and Advanced Applications - ENUMATH 2017, (2019)Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, f P- and f/P-greedy, , and . (2021)A Posteriori Error Estimation in Model Order Reduction of Elastic Multibody Systems with Large Rigid Motion, , , and . IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, Springer, (2018)Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows, , , , and . preprint, (2021)cite arxiv:2010.03030.Enabling interactive mobile simulations through distributed reduced models, , , , and . Pervasive and Mobile Computing, Elsevier BV, (2018)Non-symmetric kernel greedy interpolation., and . (2017)University of Stuttgart, in preparation, 2017..Editorial: Special Issue on Model Reduction, , and . IJNME, International Journal of Numerical Methods in Engineering, 102 (5): 931--932 (2015)Kernel Methods for Surrogate Modeling, and . ArXiv, 1907.10556. (2019)Efficient reduced models and a posteriori error estimation for parametrized dynamical systems by offline/online decomposition, and . Math. Comput. Model. Dyn. Syst., 17 (2): 145--161 (2011)