Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. - Bernard Haasdonk; Tizian Wenzel; Gabriele Santin; Syn Schmitt (ENUMATH, 2019)

A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2019)

A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows. - Pavel Gavrilenko; Bernard Haasdonk; Oleg Iliev 001; Mario Ohlberger; Felix Schindler; Pavel Toktaliev; Tizian Wenzel; Maha Youssef (LSSC, 2021)

Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. - Tizian Wenzel; Marius Kurz; Andrea Beck; Gabriele Santin; Bernard Haasdonk (LSSC, 2021)

Universality and Optimality of Structured Deep Kernel Networks. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2021)

Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, $f cdot P$- and f/P-greedy. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2021)

A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (J. Approx. Theory, 2021)

Stability of convergence rates: Kernel interpolation on non-Lipschitz domains. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2022)

Adaptive meshfree solution of linear partial differential equations with PDE-greedy kernel methods. - Tizian Wenzel; Daniel Winkle; Gabriele Santin; Bernard Haasdonk (CoRR, 2022)

Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling. - Tizian Wenzel; Bernard Haasdonk; Hendrik Kleikamp; Mario Ohlberger; Felix Schindler (LSSC, 2023)

Sharp inverse estimates for radial basis function interpolation: One-to-one correspondence between smoothness and approximation rates. - Tizian Wenzel (CoRR, 2023)

A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs. - Bernard Haasdonk; Hendrik Kleikamp; Mario Ohlberger; Felix Schindler; Tizian Wenzel (SIAM J. Sci. Comput., 2023)

Finetuning greedy kernel models by exchange algorithms. - Tizian Wenzel; Armin Iske (CoRR, 2024)

Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data. - Robin Herkert; Patrick Buchfink; Tizian Wenzel; Bernard Haasdonk; Pavel Toktaliev; Oleg Iliev 001 (CoRR, 2024)

Novel and refined stability estimates for kernel matrices. - Tizian Wenzel; Armin Iske (CoRR, 2024)

Kernel Methods in the Deep Ritz framework: Theory and practice. - Hendrik Kleikamp; Tizian Wenzel (CoRR, 2024)

On the Optimality of Target-Data-Dependent Kernel Greedy Interpolation in Sobolev Reproducing Kernel Hilbert Spaces. - Gabriele Santin; Tizian Wenzel; Bernard Haasdonk (SIAM J. Numer. Anal., 2024)

Data-Driven Kernel Designs for Optimized Greedy Schemes: A Machine Learning Perspective. - Tizian Wenzel; Francesco Marchetti; Emma Perracchione (SIAM J. Sci. Comput., 2024)

General superconvergence for kernel-based approximation. - Toni Karvonen; Gabriele Santin; Tizian Wenzel (CoRR, 2025)

A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control. - Mathias Oster; Luca Saluzzi; Tizian Wenzel (Dyn. Games Appl., 2025)

Kernel-based Greedy Approximation of Parametric Elliptic Boundary Value Problems. - Bernard Haasdonk; Gabriele Santin; Tizian Wenzel (CoRR, 2025)