| Explainable machine learning for scientific insights and discoveries R Roscher, B Bohn, MF Duarte, J Garcke Ieee Access 8, 42200-42216, 2020 | 1025 | 2020 |
| 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 | 94 | 2013 |
| A representer theorem for deep kernel learning B Bohn, M Griebel, C Rieger Journal of Machine Learning Research 20 (64), 1-32, 2019 | 72 | 2019 |
| Feasible and Successful: Genome-Wide Interaction Analysis Involving All 1.9 × 1011 Pair-Wise Interaction Tests M Steffens, T Becker, T Sander, R Fimmers, C Herold, DA Holler, C Leu, ... Human Heredity 69 (4), 268-284, 2010 | 33 | 2010 |
| Explain it to me–facing remote sensing challenges in the bio-and geosciences with explainable machine learning R Roscher, B Bohn, MF Duarte, J Garcke ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020 | 32 | 2020 |
| A sparse grid based method for generative dimensionality reduction of high-dimensional data B Bohn, J Garcke, M Griebel Journal of Computational Physics 309, 1-17, 2016 | 18 | 2016 |
| An adaptive sparse grid approach for time series prediction B Bohn, M Griebel Sparse grids and applications, 1-30, 2012 | 16 | 2012 |
| On the convergence rate of sparse grid least squares regression B Bohn Sparse Grids and Applications-Miami 2016, 19-41, 2018 | 15 | 2018 |
| Error analysis of regularized and unregularized least-squares regression on discretized function spaces B Bohn Universitäts-und Landesbibliothek Bonn, 2017 | 10 | 2017 |
| Error estimates for multivariate regression on discretized function spaces B Bohn, M Griebel SIAM Journal on Numerical Analysis 55 (4), 1843-1866, 2017 | 6 | 2017 |
| Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids B Bohn, M Griebel, J Oettershagen Proceedings of the 2019 SIAM International Conference on Data Mining, 163-171, 2019 | 5 | 2019 |
| Deep neural networks and PIDE discretizations B Bohn, M Griebel, D Kannan SIAM Journal on Mathematics of Data Science 4 (3), 1145-1170, 2022 | 3 | 2022 |
| Einbettung von Zeitreihen nach Takens’ Theorem B Bohn Diplomarbeit, Rheinische Friedrich-Wilhelms-Universität Bonn, 2010 | 2 | 2010 |
| Algorithmic mathematics in machine learning B Bohn, J Garcke, M Griebel Society for Industrial and Applied Mathematics, 2024 | 1 | 2024 |
| SIMDATA-NL-Nichtlineare Charakterisierung und Analyse von FEM-Simulationsergebnissen für Autobauteile und Crash-Tests M Griebel, HJ Bungartz, C Czado, J Garcke, U Trottenberg, CA Thole, ... Fraunhofer SCAI, 2014 | | 2014 |
| Lessons to be Learned From Genome-wide Interaction Analysis (GWIA) M Mattheisen, M Steffens, T Becker, T Sander, R Fimmers, C Herold, ... GENETIC EPIDEMIOLOGY 33 (8), 758-758, 2009 | | 2009 |
| Gerstner, T. 268 Greenberg, DA 152 Griebel, M. 268 Guo, X. 45 F Han, H He, S Herms, C Herold, M Hervella, TJ Hoffmann, DA Holler, ... | | |
Jochen GarckeUniversität Bonn, Fraunhofer SCAIVerified email at ins.uni-bonn.de