Data mining with sparse grids J Garcke, M Griebel, M Thess Computing 67 (3), 225-253, 2001 | 158 | 2001 |

Sparse grids in a nutshell J Garcke Sparse grids and applications, 57-80, 2012 | 119* | 2012 |

The combination technique and some generalisations M Hegland, J Garcke, V Challis Linear Algebra and its Applications 420 (2-3), 249-275, 2007 | 101 | 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 | 97 | 2009 |

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 | 82 | 2000 |

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 | 77 | 2013 |

Sparse grids and applications J Garcke, M Griebel Springer Science & Business Media, 2012 | 58 | 2012 |

Maschinelles Lernen durch Funktionsrekonstruktion mit verallgemeinerten dünnen Gittern J Garcke University of Bonn, Germany, 2004 | 53 | 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 | 47 | 2013 |

Regression with the optimised combination technique J Garcke Proceedings of the 23rd international conference on Machine learning, 321-328, 2006 | 43 | 2006 |

A dimension adaptive sparse grid combination technique for machine learning J Garcke ANZIAM Journal 48, 725-740, 2006 | 40 | 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 |

Semi-supervised learning with sparse grids J Garcke, M Griebel SFB 611, 2005 | 32 | 2005 |

Importance weighted inductive transfer learning for regression J Garcke, T Vanck Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014 | 30 | 2014 |

Approximating Gaussian Processes with H^2-Matrices S Börm, J Garcke European Conference on Machine Learning, 42-53, 2007 | 30 | 2007 |

Data mining with sparse grids using simplicial basis functions J Garcke, M Griebel Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001 | 28 | 2001 |

On the numerical solution of the chemical master equation with sums of rank one tensors M Hegland, J Garcke ANZIAM Journal 52, 628-643, 2010 | 25 | 2010 |

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 | 24 | 2017 |

On the parallelization of the sparse grid approach for data mining J Garcke, M Griebel International Conference on Large-Scale Scientific Computing, 22-32, 2001 | 23 | 2001 |