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ORCIDTizian Wenzel
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2020 – today
- 2024
[j4]Gabriele Santin
, Tizian Wenzel, Bernard Haasdonk:
On the Optimality of Target-Data-Dependent Kernel Greedy Interpolation in Sobolev Reproducing Kernel Hilbert Spaces. SIAM J. Numer. Anal. 62(5): 2249-2275 (2024)- [j3]Tizian Wenzel, Francesco Marchetti, Emma Perracchione:
Data-Driven Kernel Designs for Optimized Greedy Schemes: A Machine Learning Perspective. SIAM J. Sci. Comput. 46(1): 101- (2024) - [i18]Mathias Oster, Luca Saluzzi, Tizian Wenzel:
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control. CoRR abs/2402.01402 (2024) - [i17]Tizian Wenzel, Armin Iske:
Finetuning greedy kernel models by exchange algorithms. CoRR abs/2404.19487 (2024) - [i16]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 abs/2405.19170 (2024) - [i15]Tizian Wenzel, Armin Iske:
Novel and refined stability estimates for kernel matrices. CoRR abs/2409.04263 (2024) - [i14]Hendrik Kleikamp, Tizian Wenzel:
Kernel Methods in the Deep Ritz framework: Theory and practice. CoRR abs/2410.03503 (2024) - 2023
- [j2]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): 1039-1065 (2023) - [c4]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: 117-125 - [i13]Tizian Wenzel, Francesco Marchetti, Emma Perracchione:
Data-driven kernel designs for optimized greedy schemes: A machine learning perspective. CoRR abs/2301.08047 (2023) - [i12]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 abs/2302.14526 (2023) - [i11]Tizian Wenzel:
Sharp inverse estimates for radial basis function interpolation: One-to-one correspondence between smoothness and approximation rates. CoRR abs/2306.14618 (2023) - [i10]Gabriele Santin, Tizian Wenzel, Bernard Haasdonk:
On the optimality of target-data-dependent kernel greedy interpolation in Sobolev Reproducing Kernel Hilbert Spaces. CoRR abs/2307.09811 (2023) - 2022
- [i9]Tizian Wenzel, Gabriele Santin, Bernard Haasdonk:
Stability of convergence rates: Kernel interpolation on non-Lipschitz domains. CoRR abs/2203.12532 (2022) - [i8]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 abs/2204.13454 (2022) - [i7]Tizian Wenzel, Daniel Winkle, Gabriele Santin, Bernard Haasdonk:
Adaptive meshfree solution of linear partial differential equations with PDE-greedy kernel methods. CoRR abs/2207.13971 (2022) - 2021
- [j1]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: 105508 (2021) - [c3]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: 378-386 - [c2]Tizian Wenzel, Marius Kurz, Andrea Beck, Gabriele Santin, Bernard Haasdonk:
Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. LSSC 2021: 410-418 - [i6]Tizian Wenzel, Marius Kurz, Andrea Beck, Gabriele Santin, Bernard Haasdonk:
Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. CoRR abs/2103.13655 (2021) - [i5]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 abs/2104.02800 (2021) - [i4]Tizian Wenzel, Gabriele Santin, Bernard Haasdonk:
Universality and Optimality of Structured Deep Kernel Networks. CoRR abs/2105.07228 (2021) - [i3]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 abs/2105.07411 (2021) - 2020
- [i2]Bernard Haasdonk, Tizian Wenzel, Gabriele Santin, Syn Schmitt:
Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods. CoRR abs/2004.12670 (2020)
2010 – 2019
- 2019
- [c1]Bernard Haasdonk, Tizian Wenzel, Gabriele Santin, Syn Schmitt:
Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. ENUMATH 2019: 499-508 - [i1]Tizian Wenzel, Gabriele Santin, Bernard Haasdonk:
A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution. CoRR abs/1911.04352 (2019)
Coauthor Index
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