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Alla, A.; Haasdonk, B. & Schmidt, A.: Feedback control of parametrized PDEs via model order reduction and dynamic programming principle, University of Stuttgart, 2017. Zeige BibTex

Bhatt, A. & VanGorder, R.: Chaos in a non-autonomous nonlinear system describing asymmetric water wheels, 2017. Zeige BibTex

Brünnette, T.; Santin, G. & Haasdonk, B.: Greedy kernel methods for accelerating implicit integrators for parametric ODEs, University of Stuttgart, 2017. Zeige BibTex Zeige Abstract

Carlberg, K.; Brencher, L.; Haasdonk, B. & Barth, A.: Data-driven time parallelism via forecasting, 2016. Zeige BibTex

De Marchi, S.; Iske, A. & Santin, G.: Image Reconstruction from Scattered Radon Data by Weighted Positive Definite Kernel Functions, 2017. Zeige BibTex

Fehr, J.; Grunert, D.; Bhatt, A. & Hassdonk, B.: A Sensitivity Study of Error Estimation in Reduced Elastic Multibody Systems, 2017. Zeige BibTex

Fritzen, F.; Haasdonk, B.; Ryckelynck, D. & Schöps, S.: An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem, University of Stuttgart, 2016. Zeige BibTex

Geßner, T.; Haasdonk, B.; Lenz, M.; Metscher, M.; Neubauer, R.; Ohlberger, M.; Rosenbaum, W.; Rumpf, M.; Schwörer, R.; Spielberg, M. & Weikard, U.: A Procedural Interface for Multiresolutional Visualization of General Numerical Data, University of Bonn, 1999. Zeige BibTex

Haasdonk, B.: Reduzierte-Basis-Methoden, Vorlesungsskript SS 2011, University of Stuttgart, 2011. Zeige BibTex

Haasdonk, B.: Reduced Basis Methods for Parametrized PDEs -- A Tutorial Introduction for Stationary and Instationary Problems, IANS, University of Stuttgart, Germany, 2014. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Reduced Basis Method for Finite Volume Approximations of Parametrized Evolution Equations, University of Freiburg, Institute of Applied Mathematics, 2006. Zeige BibTex

Haasdonk, B.; Ohlberger, M. & Rozza, G.: A Reduced Basis Method for Evolution Schemes with Parameter-Dependent Explicit Operators, University of Münster, 2007. Zeige BibTex Zeige Abstract

Haasdonk, B.; Ohlberger, M.; Rumpf, M.; Schmidt, A. & Siebert, K.-G.: h-p-Multiresolution Visualization of Adaptive Finite Element Simulations, Mathematics Department, University of Freiburg, 2001. Zeige BibTex

Haasdonk, B.; Poluru, B. & Teynor, A.: Presto-Box 1.1 Library Documentation, IIF-LMB, Universität Freiburg, 2003. Zeige BibTex

Haasdonk, B.; Salomon, J. & Wohlmuth, B.: A Reduced Basis Method for Parametrized Variational Inequalities, University of Stuttgart, 2012. Zeige BibTex

Köppl, T.; Santin, G.; Haasdonk, B. & Helmig, R.: Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and machine learning techniques, University of Stuttgart, 2017. Zeige BibTex Zeige Abstract

Köppel, M.; Franzelin, F.; Kröker, I.; Oladyshkin, S.; Santin, G.; Wittwar, D.; Barth, A.; Haasdonk, B.; Nowak, W.; Pflüger, D. & Rohde, C.: Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario, University of Stuttgart, submitted to Comput. Geosci., 2017. Zeige BibTex Zeige Abstract

Pekalska, E. & Haasdonk, B.: Kernel Quadratic Discriminant Analysis with Positive and Indefinite Kernels, University of Münster, 2008. Zeige BibTex

Schmidt, A. & Haasdonk, B.: Data-driven surrogates of value functions and applications to feedback control for dynamical systems, University of Stuttgart, 2017. Zeige BibTex

Wirtz, D. & Haasdonk, B.: An Improved Vectorial Kernel Orthogonal Greedy Algorithm, University of Stuttgart, 2012. Zeige BibTex Zeige Abstract

Wirtz, D.; Karajan, N. & Haasdonk, B.: Model order reduction of multiscale models using kernel methods, SRC SimTech, University of Stuttgart, Germany, 2012. Zeige BibTex

Wirtz, D.; Sorensen, D. & Haasdonk, B.: A-posteriori error estimation for DEIM reduced nonlinear dynamical systems, University of Stuttgart, 2012. Zeige BibTex Zeige Abstract

Wittwar, D.; Schmidt, A. & Haasdonk, B.: Reduced Basis Approximation for the Discrete-time Parametric Algebraic Riccati Equation, University of Stuttgart, 2017. Zeige BibTex