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Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods, , , and . International Journal for Numerical Methods in Biomedical Engineering, 34 (8): e3095 (2018)Sparse approximation of regularized kernel interpolation by greedy algorithms, , and . (2019)Greedy kernel methods for accelerating implicit integrators for parametric ODEs, , and . Numerical Mathematics and Advanced Applications - ENUMATH 2017, 126, Cham, Springer, (2018)Convergence rate of the data-independent P-greedy algorithm in kernel-based approximation, and . Dolomites Research Notes on Approximation. Special Issues, (2017)Partition of unity interpolation using stable kernel-based techniques, , , , and . New Trends in Numerical Analysis: Theory, Methods, Algorithms and Applications (NETNA 2015), 116, page 95-107. Amsterdam, Elsevier, (2017)Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario, , , , , , , , , and 1 other author(s). Computational Geosciences, 23 (2): 339--354 (Apr 1, 2019)Greedy regularized kernel interpolation, , and . arXiv preprint arXiv:1807.09575, (2018)Approximating basins of attraction for dynamical systems via stable radial bases, , , , and . International Conference on Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015), 1738, 1, page 390003. Melville, NY, AIP Publishing, (2016)Approximation in kernel-based spaces, optimal subspaces and approximationof eigenfunction. University of Padova, Padua, Dissertation, (2016)Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and machine learning techniques., , , and . CoRR, (2018)