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Publications

Recent PrePrints

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

Haasdonk, B. & Santin, G.: Greedy Kernel Approximation for Sparse Surrogate Modelling, 2017. Zeige BibTex

Tempel, P.; Schmidt, A.; Haasdonk, B. & Pott, A.: Application of the Rigid Finite Element Method to the Simulation of Cable-Driven Parallel Robots, University of Stuttgart, 2017. Zeige BibTex

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

Alla, A.; Schmidt, A. & Haasdonk, B.: Model order reduction approaches for infinite horizon optimal control problems via the HJB equation, University of Stuttgart, 2016. Zeige BibTex Zeige Abstract

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

Publications

Dibak, C.; Schmidt, A.; Dürr, F.; Haasdonk, B. & Rothermel, K.: Server-Assisted Interactive Mobile Simulations for Pervasive Applications, Proceedings of the 15th IEEE International Conference on Pervasive Computing and Communications (PerCom), University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany, IEEE, 2017, 1-10. Zeige BibTex Zeige Abstract

Martini, I.; Rozza, G. & Haasdonk, B.: Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models, Journal of Scientific Computing, 2017. Zeige BibTex

Santin, G. & Haasdonk, B.: Convergence rate of the data-independent P-greedy algorithm in kernel-based approximation, Dolomites Research Notes on Approximation, 2017, 10, 68-78. Zeige BibTex Zeige Abstract

Schmidt, A. & Haasdonk, B.: Reduced basis approximation of large scale parametric algebraic Riccati equations, ESAIM: Control, Optimisation and Calculus of Variations, EDP Sciences, 2017. Zeige BibTex

Amsallem, D. & Haasdonk, B.: PEBL-ROM: Projection-Error Based Local Reduced-Order Models, AMSES, Advanced Modeling and Simulation in Engineering Sciences, 2016, 3. Zeige BibTex

Antoulas, A. C.; Haasdonk, B. & Peherstorfer, B.: MORML 2016 Book of Abstracts, University of Stuttgart, 2016. Zeige BibTex

Baur, U.; Benner, P.; Haasdonk, B.; Himpe, C.; Maier, I. & Ohlberger, M.: P. Benner and A. Cohen and M. Ohlberger and K. Willcox (Eds.), Comparison of methods for parametric model order reduction of instationary problems, Model Reduction and Approximation for Complex Systems, Birkhäuser Publishing, 2016. Zeige BibTex

Garmatter, D.; Haasdonk, B. & Harrach, B.: A reduced Landweber Method for Nonlinear Inverse Problems, Inverse Problems, 2016, 32, 1-21. Zeige BibTex

Redeker, M. & Haasdonk, B.: A POD-EIM reduced two-scale model for precipitation in porous media, MCMDS, Mathematical and Computer Modelling of Dynamical Systems, 2016. Zeige BibTex

Schmidt, A. & Haasdonk, B.: Reduced basis method for H2 optimal feedback control problems, IFAC-PapersOnLine, 2016, 49, 327 - 332. Zeige BibTex Zeige Abstract

Amsallem, D.; Farhat, C. & Haasdonk, B.: Editorial: Special Issue on Modelling Reduction, IJNME, International Journal of Numerical Methods in Engineering, 2015, 102, 931-932. Zeige BibTex

Burkovska, O.; Haasdonk, B.; Salomon, J. & Wohlmuth, B.: Reduced basis methods for pricing options with the Black-Scholes and Heston model, SIAM journal on Financial Mathematics (SIFIN), Arxiv, 2015. Zeige BibTex

Dihlmann, M. A. & Haasdonk, B.: Certified PDE-constrained parameter optimization using reduced basis surrogate models for evolution problems, COAP, Computational Optimization and Applications, 2015, 60, 753-787. Zeige BibTex

Dihlmann, M. & Haasdonk, B.: A reduced basis Kalman filter for parametrized partial differential equations, ESAIM: Control, Optimisation and Calculus of Variations, EDP Sciences, 2015. Zeige BibTex

Kaulmann, S.; Flemisch, B.; Haasdonk, B.; Lie, K.-A. & Ohlberger, M.: The Localized Reduced Basis Multiscale method for two-phase flows in porous media, Internat. J. Numer. Methods Engrg., 2015, 102, 1018-1040. Zeige BibTex

Martini, I. & Haasdonk, B.: Output Error Bounds for the Dirichlet-Neumann Reduced Basis Method, Numerical Mathematics and Advanced Applications - ENUMATH 2013, 2015, 103, 437-445. Zeige BibTex

Martini, I.; Rozza, G. & Haasdonk, B.: Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system, Advances in Computational Mathematics, 2015, 41, 1131-1157. Zeige BibTex

Redeker, M. & Haasdonk, B.: A POD-EIM reduced two-scale model for crystal growth, Advances in Computational Mathematics, Springer US, 2015, 41, 987-1013. Zeige BibTex Zeige Abstract

Schmidt, A.; Dihlmann, M. & Haasdonk, B.: Basis generation approaches for a reduced basis linear quadratic regulator, Proc. MATHMOD 2015 - 8th Vienna International Conference on Mathematical Modelling, 2015, 713-718. Zeige BibTex

Wirtz, D.; Karajan, N. & Haasdonk, B.: Surrogate Modelling of multiscale models using kernel methods, International Journal of Numerical Methods in Engineering, 2015, 101, 1-28. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Wenn die Probleme zahlreicher werden: Reduzierte Basis Methoden für effiziente und gesicherte numerische Simulation, GAMM Rundbrief, 2014, 2014, 6-13. Zeige BibTex

Kaulmann, S.; Flemisch, B.; Haasdonk, B.; Lie, K.-A. & Ohlberger, M.: The Localized Reduced Basis Multiscale method for two-phase flows in porous media, arXiv.org, 2014. Kaulmann2014wa.pdf Zeige BibTex Zeige Abstract

Maier, I. & Haasdonk, B.: A Dirichlet-Neumann reduced basis method for homogeneous domain decomposition problems, Applied Numerical Mathematics, 2014, 78, 31-48. Zeige BibTex

Wirtz, D.; Sorensen, D. & Haasdonk, B.: A Posteriori Error Estimation for DEIM Reduced Nonlinear Dynamical Systems, SIAM Journal on Scientific Computing, Society for Industrial & Applied Mathematics (SIAM), 2014, 36, A311-A338. Zeige BibTex

Wirtz, D.; Sorensen, D. & Haasdonk, B.: A-posteriori error estimation for DEIM reduced nonlinear dynamical systems, SIAM J. Sci. Comp., University of Stuttgart, 2014, 36, A311-A338. Zeige BibTex Zeige Abstract

Amsallem, D.; Haasdonk, B. & Rozza, G.: A Conference within a Conference for MOR Researchers, SIAM News, 2013, 46, 8. Zeige BibTex

Dihlmann, M. & Haasdonk, B.: Certified Nonlinear Parameter Optimization with Reduced Basis Surrogate Models, PAMM, Proc. Appl. Math. Mech., Special Issue: 84th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Novi Sad 2013; Editors: L. Cvetković, T. Atanacković and V. Kostić, 2013, 13, 3-6. Zeige BibTex

Dihlmann, M. & Haasdonk, B.: Certified Nonlinear Parameter Optimization with Reduced Basis Surrogate Models, PAMM, Proc. Appl. Math. Mech., Special Issue: 84th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Novi Sad 2013; Editors: L. Cvetković, T. Atanacković and V. Kostić, 2013, 13, 3-6. Zeige BibTex

Fehr, J.; Fischer, M.; Haasdonk, B. & Eberhard, P.: Greedy-based Approximation of Frequency-weighted Gramian Matrices for Model Reduction in Multibody Dynamics, ZAMM, 2013, 93, 501-519. Zeige BibTex

Haasdonk, B.: Convergence Rates of the POD--Greedy Method, ESAIM: Mathematical Modelling and Numerical Analysis, EDP Sciences, 2013, 47, 859-873. Zeige BibTex Zeige Abstract

Haasdonk, B.; Urban, K. & Wieland, B.: Reduced basis methods for parametrized partial differential equations with stochastic influences using the Karhunen Loeve expansion, SIAM/ASA J. Unc. Quant., 2013, 1, 79-105. Zeige BibTex

Kaulmann, S. & Haasdonk, B.: Moitinho de Almeida, José Paulo Baptista and Diez, Pedro and Tiago, Carlos and Parés, Núria (Eds.), Online Greedy Reduced Basis Construction Using Dictionaries, VI International Conference on Adaptive Modeling and Simulation (ADMOS 2013), 2013, 365-376. Zeige BibTex Zeige Abstract

Wirtz, D. & Haasdonk, B.: A Vectorial Kernel Orthogonal Greedy Algorithm, Dolomites Res. Notes Approx., 2013, 6, 83-100. Zeige BibTex Zeige Abstract

Albrecht, F.; Haasdonk, B.; Kaulmann, S. & Ohlberger, M.: Handloviv cová, Angela and Minarechová, Zuzana and v Sevv coviv c, Daniel (Eds.), The Localized Reduced Basis Multiscale Method, Algoritmy 2012, Publishing House of STU, 2012, 393-403. Zeige BibTex Zeige Abstract

Dihlmann, M.; Kaulmann, S. & Haasdonk, B.: Online Reduced Basis Construction Procedure for Model Reduction of Parametrized Evolution Systems, Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling, 2012. Zeige BibTex

Drohmann, M.; Haasdonk, B. & Ohlberger, M.: Dedner, Andreas and Flemisch, Bernd and Klöfkorn, Robert (Eds.), A Software Framework for Reduced Basis Methods Using DUNE-RB and RBMATLAB, Advances in DUNE: Proceedings of the DUNE User Meeting, Held in October 6th-8th 2010 in Stuttgart, Germany, Springer, 2012. Zeige BibTex Zeige Abstract

Drohmann, M.; Haasdonk, B. & Ohlberger, M.: Reduced Basis Model Reduction of Parametrized Two-phase Flow in Porous Media, Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling, 2012. Zeige BibTex

Drohmann, M.; Haasdonk, B. & Ohlberger, M.: Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation, SIAM J. Sci. Comput., 2012, 34, A937-A969. Zeige BibTex Zeige Abstract

Haasdonk, B.; Salomon, J. & Wohlmuth, B.: A Reduced Basis Method for Parametrized Variational Inequalities, SIAM Journal on Numerical Analysis, 2012, 50, 2656-2676. Zeige BibTex

Haasdonk, B.; Salomon, J. & Wohlmuth, B.: A Reduced Basis Method for the Simulation of American Options, ENUMATH 2011 Proceedings, 2012. Zeige BibTex

Ruiner, T.; Fehr, J.; Haasdonk, B. & Eberhard, P.: A-posteriori error estimation for second order mechanical systems, Acta Mechanica Sinica, 2012, 28(3), 854-862. Zeige BibTex

Waldherr, S. & Haasdonk, B.: Efficient Parametric Analysis of the Chemical Master Equation through Model Order Reduction, BMC Systems Biology, 2012, 6, 81. Zeige BibTex

Wirtz, D. & Haasdonk, B.: A-posteriori error estimation for parameterized kernel-based systems, Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling, 2012. Zeige BibTex Zeige Abstract

Wirtz, D. & Haasdonk, B.: Efficient a-posteriori error estimation for nonlinear kernel-based reduced systems, Systems and Control Letters, 2012, 61, 203 - 211. Zeige BibTex Zeige Abstract

Dihlmann, M.; Drohmann, M. & Haasdonk, B.: Model Reduction of Parametrized Evolution Problems using the Reduced basis Method with Adaptive Time-Partitioning, Proc. of ADMOS 2011, 2011. Zeige BibTex

Drohmann, M.; Haasdonk, B. & Ohlberger, M.: Adaptive Reduced Basis Methods for Nonlinear Convection-Diffusion Equations, In Proc. FVCA6, 2011. Zeige BibTex

Haasdonk, B.; Dihlmann, M. & Ohlberger, M.: A Training Set and Multiple Basis Generation Approach for Parametrized Model Reduction Based on Adaptive Grids in Parameter Space, Mathematical and Computer Modelling of Dynamical Systems, 2011, 17, 423-442. Zeige BibTex

Haasdonk, B. & Lohmann, B.: Special Issue on ''Model Order Reduction of Parametrized Problems'', Mathematical and Computer Modelling of Dynamical Systems, 2011, 17, 295-296. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Efficient reduced models and it a posteriori error estimation for parametrized dynamical systems by offline/online decomposition, Math. Comput. Model. Dyn. Syst., 2011, 17, 145-161. Zeige BibTex

Jung, N.; Patera, A.; Haasdonk, B. & Lohmann, B.: Model Order Reduction and Error Estimation with an Application to the Parameter-Dependent Eddy Current Equation, Mathematical and Computer Modelling of Dynamical Systems, 2011, 17, 561-582. Zeige BibTex

Kaulmann, S.; Ohlberger, M. & Haasdonk, B.: A new local reduced basis discontinuous Galerkin approach for heterogeneous multiscale problems, Comptes Rendus Mathematique, 2011, 349, 1233-1238. Zeige BibTex Zeige Abstract

Haasdonk, B.: Effiziente und Gesicherte Modellreduktion für Parametrisierte Dynamische Systeme., at - Automatisierungstechnik, 2010, 58, 468-474. Zeige BibTex

Pekalska, E. & Haasdonk, B.: Indefinite Kernel Discriminant Analysis, Proc. COMPSTAT 2010, International Conference on Computational Statistics, 2010. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Space-Adaptive Reduced Basis Simulation for Time-Dependent Problems, Proc. MATHMOD 2009, 6th Vienna International Conference on Mathematical Modelling, 2009. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Efficient Reduced Models for Parametrized Dynamical Systems by Offline/Online Decomposition, Proc. MATHMOD 2009, 6th Vienna International Conference on Mathematical Modelling, 2009. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Efficient a-posteriori Error Estimation for Parametrized Reduced Dynamical Systems, GMA-Fachaussschuss 1.30, Tagungsband, 2009. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Reduced basis method for explicit finite volume approximations of nonlinear conservation laws, Hyperbolic problems: theory, numerics and applications, Amer. Math. Soc., 2009, 67, 605-614. Zeige BibTex

Haasdonk, B.; Ohlberger, M.; Tonn, T. & Urban, K.: MoRePaS 2009 Book of Abstracts, University of Münster, 2009. Zeige BibTex

Jung, N.; Haasdonk, B. & Kröner, D.: Reduced Basis Method for Quadratically Nonlinear Transport Equations, IJCSM, 2009, 2, 334-353. Zeige BibTex

Pekalska, E. & Haasdonk, B.: Kernel Discriminant Analysis with Positive Definite and Indefinite Kernels, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31, 1017-1032. Zeige BibTex

Drohmann, M.; Haasdonk, B. & Ohlberger, M.: Reduced Basis Method for Finite Volume Approximation of Evolution Equations on Parametrized Geometries, Proceedings of ALGORITMY 2009, 2008, 111-120. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Reduced basis method for finite volume approximations of parametrized linear evolution equations, ESAIM: M2AN, 2008, 42, 277-302. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: Adaptive basis enrichment for the reduced basis method applied to finite volume schemes, Finite volumes for complex applications V, ISTE, London, 2008, 471-478. Zeige BibTex

Haasdonk, B.; Ohlberger, M. & Rozza, G.: A Reduced Basis Method for Evolution Schemes with Parameter-Dependent Explicit Operators, ETNA, Electronic Transactions on Numerical Analysis, 2008, 32, 145-161. Zeige BibTex

Haasdonk, B. & Pekalska, E.: Indefinite Kernel Fisher Discriminant, Proc. ICPR 2008, International Conference on Pattern Recognition, 2008. Zeige BibTex

Haasdonk, B. & Pekalska, E.: Classification with Kernel Mahalanobis Distances, Proc. of 32nd. GfKl Conference, Advances in Data Analysis, Data Handling and Business Intelligence, 2008. Zeige BibTex

Fuhrmann J; Haasdonk, B.; Holzbecher, E. & Ohlberger, M.: Guest Editorial for Special Issue on Modelling and Simulation of PEM-FC, Journal of Fuel Cell Science and Technology, 2007. Zeige BibTex

Haasdonk, B. & Burkhardt, H.: Classification with Invariant Distance Substitution Kernels, Proc. of 31st GfKl Conference, Data Analysis, Machine Learning, and Applications, 2007. Zeige BibTex

Haasdonk, B. & Burkhardt, H.: Invariant Kernels for Pattern Analysis and Machine Learning, Machine Learning, IIF-LMB, Universität Freiburg, Institut für Informatik, 2007, 68, 35-61. Zeige BibTex

Haasdonk, B. & Ohlberger, M.: P. Díez and K. Runesson (Eds.), Basis Construction for Reduced Basis Methods By Adaptive Parameter Grids, Proc. International Conference on Adaptive Modeling and Simulation, ADMOS 2007, CIMNE, Barcelona, 2007. Zeige BibTex Zeige Abstract

Peschke, K.-D.; Haasdonk, B.; Ronneberger, O.; Burkhard, H.; Rösch, P.; Harz, M. & Popp, J.: Using Transformation Knowledge for the Classification of Raman Spectra of Biological Samples, BIOMED 2006, Proc. of the 4th IASTED International Conference on Biomedical Engineering, 2006, 288-293. Zeige BibTex

Haasdonk, B.: Feature Space Interpretation of SVMs with Indefinite Kernels, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, 2005, 27, 482-492. Zeige BibTex

Haasdonk, B.; Vossen, A. & Burkhardt, H.: Invariance in Kernel Methods by Haar-Integration Kernels, Proceedings of the 14th Scandinavian Conference on Image Analysis, Springer, 2005. Zeige BibTex

Haasdonk, B. & Bahlmann, C.: Learning with Distance Substitution Kernels, Pattern Recognition - Proceedings of the 26th DAGM Symposium, Springer, 2004, 220-227. Zeige BibTex

Haasdonk, B.; Halawani, A. & Burkhardt, H.: Adjustable invariant features by partial Haar-integration, Proceedings of the 17th International Conference on Pattern Recognition, 2004, 2, 769- 774. Zeige BibTex

Haasdonk, B.; Ohlberger, M.; Rumpf, M.; Schmidt, A. & Siebert, K. G.: Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations, Computing, 2003, 70, 181-204. Zeige BibTex Zeige Abstract

Bahlmann, C.; Haasdonk, B. & Burkhardt, H.: On-line Handwriting Recognition with Support Vector Machines - A Kernel Approach, Proc. of the 8th International Workshop on Frontiers in Handwriting Recognition, IEEE Computer Society, 2002, 49-54. Zeige BibTex Zeige Abstract

Haasdonk, B. & Keysers, D.: Tangent Distance Kernels for Support Vector Machines, Proceedings of the 16th International Conference on Pattern Recognition, IEEE Computer Society, 2002, 2, 864-868. Zeige BibTex Zeige Abstract

Haasdonk, B.; Kröner, D. & Rohde, C.: Convergence of a staggered Lax-Friedrichs scheme for nonlinear conservation laws on unstructured two-dimensional grids, Numer. Math., 2001, 88, 459-484. Zeige BibTex

Haasdonk, B.: Convergence of a Staggered Lax-Friedrichs Scheme on Unstructured 2D-Grids, HYP 2000, Proceedings of the 8th International Conference on Hyperbolic Problems, Birkhäuser, 2000, 2, 475-484. Zeige BibTex