Bernard Haasdonk

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 54

Top Venues

CoRR

Adv. Comput. Math.

LSSC

SIAM J. Sci. Comput.

University of Freiburg, Freiburg im Breisgau, Germany (PHD)

Education History

University of Freiburg, Freiburg im Breisgau, Germany

PHD

Publications

Robin Herkert, Patrick Buchfink, Bernard Haasdonk
Dictionary-based online-adaptive structure-preserving model order reduction for parametric Hamiltonian systems. Adv. Comput. Math. 50 (1) (2024)
Robin Herkert, Patrick Buchfink, Bernard Haasdonk, Johannes Rettberg, Jörg Fehr
Error Analysis of Randomized Symplectic Model Order Reduction for Hamiltonian systems. CoRR (2024)
Tobias Ehring, Bernard Haasdonk
Hermite kernel surrogates for the value function of high-dimensional nonlinear optimal control problems. Adv. Comput. Math. 50 (3) (2024)
Robin Herkert, Patrick Buchfink, Tizian Wenzel, Bernard Haasdonk, Pavel Toktaliev, Oleg Iliev
Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data. CoRR (2024)
Robin Herkert, Patrick Buchfink, Bernard Haasdonk
Dictionary-based Online-adaptive Structure-preserving Model Order Reduction for Parametric Hamiltonian Systems. CoRR (2023)
Patrick Buchfink, Silke Glas, Bernard Haasdonk
Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds. CoRR (2023)
Robin Herkert, Patrick Buchfink, Bernard Haasdonk, Johannes Rettberg, Jörg Fehr
Randomized Symplectic Model Order Reduction for Hamiltonian Systems. CoRR (2023)
Patrick Buchfink, Silke Glas, Bernard Haasdonk
Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder. SIAM J. Sci. Comput. 45 (2) (2023)
Tizian Wenzel, Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler
Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling. LSSC (2023)
Robin Herkert, Patrick Buchfink, Bernard Haasdonk, Johannes Rettberg, Jörg Fehr
Randomized Symplectic Model Order Reduction for Hamiltonian Systems. LSSC (2023)
Gabriele Santin, Tizian Wenzel, Bernard Haasdonk
On the optimality of target-data-dependent kernel greedy interpolation in Sobolev Reproducing Kernel Hilbert Spaces. CoRR (2023)
Tobias Ehring, Bernard Haasdonk
Hermite kernel surrogates for the value function of high-dimensional nonlinear optimal control problems. CoRR (2023)
Tizian Wenzel, Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler
Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling. CoRR (2023)
Patrick Buchfink, Silke Glas, Bernard Haasdonk, Benjamin Unger
Model Reduction on Manifolds: A differential geometric framework. CoRR (2023)
Johannes Rettberg, Dominik Wittwar, Patrick Buchfink, Robin Herkert, Jörg Fehr, Bernard Haasdonk
Improved a posteriori Error Bounds for Reduced port-Hamiltonian Systems. CoRR (2023)
Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler, Tizian Wenzel
A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs. SIAM J. Sci. Comput. 45 (3) (2023)
Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler, Tizian Wenzel
A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs. CoRR (2022)
Raphael Leiteritz, Patrick Buchfink, Bernard Haasdonk, Dirk Pflüger
Surrogate-data-enriched Physics-Aware Neural Networks. NLDL (2022)
Johannes Rettberg, Dominik Wittwar, Patrick Buchfink, Alexander Brauchler, Pascal Ziegler, Jörg Fehr, Bernard Haasdonk
Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. CoRR (2022)
Tizian Wenzel, Daniel Winkle, Gabriele Santin, Bernard Haasdonk
Adaptive meshfree solution of linear partial differential equations with PDE-greedy kernel methods. CoRR (2022)
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
Stability of convergence rates: Kernel interpolation on non-Lipschitz domains. CoRR (2022)
Patrick Buchfink, Silke Glas, Bernard Haasdonk
Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds. CoRR (2021)
Bernard Haasdonk, Mario Ohlberger, Felix Schindler
An adaptive model hierarchy for data-augmented training of kernel models for reactive flow. CoRR (2021)
Shahnewaz Shuva, Patrick Buchfink, Oliver Röhrle, Bernard Haasdonk
Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue. CoRR (2021)
Raphael Leiteritz, Patrick Buchfink, Bernard Haasdonk, Dirk Pflüger
Surrogate-data-enriched Physics-Aware Neural Networks. CoRR (2021)
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution. J. Approx. Theory 262 (2021)
Shahnewaz Shuva, Patrick Buchfink, Oliver Röhrle, Bernard Haasdonk
Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue. LSSC (2021)
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, $f \cdot P$- and f/P-greedy. CoRR (2021)
Tizian Wenzel, Marius Kurz, Andrea Beck, Gabriele Santin, Bernard Haasdonk
Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. CoRR (2021)
Pavel Gavrilenko, Bernard Haasdonk, Oleg Iliev, Mario Ohlberger, Felix Schindler, Pavel Toktaliev, Tizian Wenzel, Maha Youssef
A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows. LSSC (2021)
Tizian Wenzel, Marius Kurz, Andrea Beck, Gabriele Santin, Bernard Haasdonk
Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. LSSC (2021)
Pavel Gavrilenko, Bernard Haasdonk, Oleg Iliev, Mario Ohlberger, Felix Schindler, Pavel Toktaliev, Tizian Wenzel, Maha Youssef
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows. CoRR (2021)
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
Universality and Optimality of Structured Deep Kernel Networks. CoRR (2021)
Andreas Schmidt, Dominik Wittwar, Bernard Haasdonk
Rigorous and effective a-posteriori error bounds for nonlinear problems - application to RB methods. Adv. Comput. Math. 46 (2) (2020)
Gabriele Santin, Toni Karvonen, Bernard Haasdonk
Sampling based approximation of linear functionals in Reproducing Kernel Hilbert Spaces. CoRR (2020)
Bernard Haasdonk, Boumediene Hamzi, Gabriele Santin, Dominik Wittwar
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem. CoRR (2020)
Alessandro Alla, Bernard Haasdonk, Andreas Schmidt
Feedback control of parametrized PDEs via model order reduction and dynamic programming principle. Adv. Comput. Math. 46 (1) (2020)
Bernard Haasdonk, Tizian Wenzel, Gabriele Santin, Syn Schmitt
Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods. CoRR (2020)
Patrick Buchfink, Bernard Haasdonk
Experimental Comparison of Symplectic and Non-symplectic Model Order Reduction on an Uncertainty Quantification Problem. ENUMATH (2019)
Gabriele Santin, Bernard Haasdonk
Kernel Methods for Surrogate Modeling. CoRR (2019)
Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
Data-Driven Time Parallelism via Forecasting. SIAM J. Sci. Comput. 41 (3) (2019)
Bernard Haasdonk, Tizian Wenzel, Gabriele Santin, Syn Schmitt
Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. ENUMATH (2019)
Tizian Wenzel, Gabriele Santin, Bernard Haasdonk
A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution. CoRR (2019)
Roman Föll, Bernard Haasdonk, Markus Hanselmann, Holger Ulmer
Deep recurrent Gaussian process with variational Sparse Spectrum approximation. CoRR (2019)
Dominik Wittwar, Bernard Haasdonk
Convergence Rates for Matrix P-Greedy Variants. ENUMATH (2019)
Christoph Dibak, Bernard Haasdonk, Andreas Schmidt, Frank Dürr, Kurt Rothermel
Enabling interactive mobile simulations through distributed reduced models. Pervasive Mob. Comput. 45 (2018)
Tobias Köppl, Gabriele Santin, Bernard Haasdonk, Rainer Helmig
Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and machine learning techniques. CoRR (2018)
Markus Köppel, Fabian Franzelin, Ilja Kröker, Sergey Oladyshkin, Gabriele Santin, Dominik Wittwar, Andrea Barth, Bernard Haasdonk, Wolfgang Nowak, Dirk Pflüger, Christian Rohde
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. CoRR (2018)
Immanuel Martini, Bernard Haasdonk, Gianluigi Rozza
Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models. J. Sci. Comput. 74 (1) (2018)
Christoph Dibak, Bernard Haasdonk, Andreas Schmidt, Frank Dürr, Kurt Rothermel
Enabling Interactive Mobile Simulations Through Distributed Reduced Models. CoRR (2018)
Christoph Dibak, Andreas Schmidt, Frank Dürr, Bernard Haasdonk, Kurt Rothermel
Server-assisted interactive mobile simulations for pervasive applications. PerCom (2017)
Felix Fritzen, Bernard Haasdonk, David Ryckelynck, Sebastian Schöps
An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem. CoRR (2016)
Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
Data-driven time parallelism via forecasting. CoRR (2016)
David Amsallem, Bernard Haasdonk
PEBL-ROM: Projection-error based local reduced-order models. Adv. Model. Simul. Eng. Sci. 3 (1) (2016)
O. Burkovska, Bernard Haasdonk, Julien Salomon, Barbara I. Wohlmuth
Reduced Basis Methods for Pricing Options with the Black-Scholes and Heston Models. SIAM J. Financial Math. 6 (1) (2015)
Markus A. Dihlmann, Bernard Haasdonk
Certified PDE-constrained parameter optimization using reduced basis surrogate models for evolution problems. Comput. Optim. Appl. 60 (3) (2015)
Magnus Redeker, Bernard Haasdonk
A POD-EIM reduced two-scale model for crystal growth. Adv. Comput. Math. 41 (5) (2015)
Immanuel Martini, Gianluigi Rozza, Bernard Haasdonk
Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system. Adv. Comput. Math. 41 (5) (2015)
Daniel Wirtz, Danny C. Sorensen, Bernard Haasdonk
A Posteriori Error Estimation for DEIM Reduced Nonlinear Dynamical Systems. SIAM J. Sci. Comput. 36 (2) (2014)
Bernard Haasdonk, Karsten Urban, Bernhard Wieland
Reduced Basis Methods for Parameterized Partial Differential Equations with Stochastic Influences Using the Karhunen-Loève Expansion. SIAM/ASA J. Uncertain. Quantification 1 (1) (2013)
Immanuel Martini, Bernard Haasdonk
Output Error Bounds for the Dirichlet-Neumann Reduced Basis Method. ENUMATH (2013)
Bernard Haasdonk, Julien Salomon, Barbara I. Wohlmuth
A Reduced Basis Method for Parametrized Variational Inequalities. SIAM J. Numer. Anal. 50 (5) (2012)
Steffen Waldherr, Bernard Haasdonk
Efficient parametric analysis of the chemical master equation through model order reduction. BMC Syst. Biol. 6 (2012)
Daniel Wirtz, Bernard Haasdonk
Efficient a-posteriori error estimation for nonlinear kernel-based reduced systems. Syst. Control. Lett. 61 (1) (2012)
Martin Drohmann, Bernard Haasdonk, Mario Ohlberger
Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation. SIAM J. Sci. Comput. 34 (2) (2012)
Bernard Haasdonk, Elzbieta Pekalska
Indefinite Kernel Discriminant Analysis. COMPSTAT (2010)
Bernard Haasdonk
Effiziente und gesicherte Modellreduktion für parametrisierte dynamische Systeme (Efficient and Certified Model Reduction for Parametrized Dynamical Systems). Autom. 58 (8) (2010)
Elzbieta Pekalska, Bernard Haasdonk
Kernel Discriminant Analysis for Positive Definite and Indefinite Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 31 (6) (2009)
Nadine Jung, Bernard Haasdonk, Dietmar Kröner
Reduced Basis Method for quadratically nonlinear transport equations. Int. J. Comput. Sci. Math. 2 (4) (2009)
Bernard Haasdonk, Elzbieta Pekalska
Classification with Kernel Mahalanobis Distance Classifiers. GfKl (2008)
Bernard Haasdonk, Elzbieta Pekalska
Indefinite Kernel Fisher Discriminant. ICPR (2008)
Bernard Haasdonk, Hans Burkhardt
Invariant kernel functions for pattern analysis and machine learning. Mach. Learn. 68 (1) (2007)
Bernard Haasdonk, Hans Burkhardt
Classification with Invariant Distance Substitution Kernels. GfKl (2007)
Bernard Haasdonk, A. Vossen, Hans Burkhardt
Invariance in Kernel Methods by Haar-Integration Kernels. SCIA (2005)
Bernard Haasdonk
Feature Space Interpretation of SVMs with Indefinite Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 27 (4) (2005)
Bernard Haasdonk, Claus Bahlmann
Learning with Distance Substitution Kernels. DAGM-Symposium (2004)
Bernard Haasdonk, Alaa Halawani, Hans Burkhardt
Adjustable Invariant Features by Partial Haar-Integration. ICPR (2) (2004)
Bernard Haasdonk, Mario Ohlberger, Martin Rumpf, Alfred Schmidt, Kunibert G. Siebert
Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations. Computing 70 (3) (2003)
Bernard Haasdonk, Daniel Keysers
Tangent Distance Kernels for Support Vector Machines. ICPR (2) (2002)
Claus Bahlmann, Bernard Haasdonk, Hans Burkhardt
Online handwriting recognition with support vector machines - a kernel approach. IWFHR (2002)
Bernard Haasdonk, Dietmar Kröner, Christian Rohde
Convergence of a staggered Lax-Friedrichs scheme for nonlinear conservation laws on unstructured two-dimensional grids. Numerische Mathematik 88 (3) (2001)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bernard Haasdonk