| Data mining with sparse grids J Garcke, M Griebel, M Thess Computing 67 (3), 225-253, 2001 | 161 | 2001 |
| Sparse grids in a nutshell J Garcke Sparse grids and applications, 57-80, 2012 | 128* | 2012 |
| The combination technique and some generalisations M Hegland, J Garcke, V Challis Linear Algebra and its Applications 420 (2-3), 249-275, 2007 | 100 | 2007 |
| Multivariate regression and machine learning with sums of separable functions G Beylkin, J Garcke, MJ Mohlenkamp SIAM Journal on Scientific Computing 31 (3), 1840-1857, 2009 | 99 | 2009 |
| An adaptive sparse grid semi-Lagrangian scheme for first order Hamilton-Jacobi Bellman equations O Bokanowski, J Garcke, M Griebel, I Klompmaker Journal of Scientific Computing 55 (3), 575-605, 2013 | 86 | 2013 |
| On the computation of the eigenproblems of hydrogen and helium in strong magnetic and electric fields with the sparse grid combination technique J Garcke, M Griebel Journal of Computational Physics 165 (2), 694-716, 2000 | 83 | 2000 |
| Sparse grids and applications J Garcke, M Griebel Springer Science & Business Media, 2012 | 63 | 2012 |
| Maschinelles Lernen durch Funktionsrekonstruktion mit verallgemeinerten dünnen Gittern J Garcke University of Bonn, Germany, 2004 | 56 | 2004 |
| Classification with sparse grids using simplicial basis functions J Garcke, M Griebel Intelligent data analysis 6 (6), 483-502, 2002 | 52 | 2002 |
| Analysis of car crash simulation data with nonlinear machine learning methods B Bohn, J Garcke, R Iza-Teran, A Paprotny, B Peherstorfer, ... Procedia Computer Science 18, 621-630, 2013 | 51 | 2013 |
| Explainable machine learning for scientific insights and discoveries R Roscher, B Bohn, MF Duarte, J Garcke IEEE Access 8, 42200-42216, 2020 | 47 | 2020 |
| Regression with the optimised combination technique J Garcke Proceedings of the 23rd international conference on Machine learning, 321-328, 2006 | 44 | 2006 |
| A dimension adaptive sparse grid combination technique for machine learning J Garcke ANZIAM Journal 48, 725-740, 2006 | 41 | 2006 |
| Fitting multidimensional data using gradient penalties and the sparse grid combination technique J Garcke, M Hegland Computing 84 (1-2), 1-25, 2009 | 38 | 2009 |
| Informed Machine Learning--A Taxonomy and Survey of Integrating Knowledge into Learning Systems L von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ... arXiv preprint arXiv:1903.12394, 2019 | 35* | 2019 |
| Importance weighted inductive transfer learning for regression J Garcke, T Vanck Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014 | 35 | 2014 |
| Semi-supervised learning with sparse grids J Garcke, M Griebel SFB 611, 2005 | 34 | 2005 |
| Data mining with sparse grids using simplicial basis functions J Garcke, M Griebel Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001 | 30 | 2001 |
| Approximating Gaussian Processes with H^2-Matrices S Börm, J Garcke European Conference on Machine Learning, 42-53, 2007 | 29 | 2007 |
| Suboptimal feedback control of PDEs by solving HJB equations on adaptive sparse grids J Garcke, A Kröner Journal of Scientific Computing 70 (1), 1-28, 2017 | 28 | 2017 |
