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Jochen Garcke
Jochen Garcke
Universität Bonn, Fraunhofer SCAI
Bestätigte E-Mail-Adresse bei ins.uni-bonn.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Explainable machine learning for scientific insights and discoveries
R Roscher, B Bohn, MF Duarte, J Garcke
Ieee Access 8, 42200-42216, 2020
3022020
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
186*2019
Data mining with sparse grids
J Garcke, M Griebel, M Thess
Computing 67 (3), 225-253, 2001
1762001
Sparse grids in a nutshell
J Garcke
Sparse grids and applications, 57-80, 2012
164*2012
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
1172009
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
1082013
The combination technique and some generalisations
M Hegland, J Garcke, V Challis
Linear Algebra and its Applications 420 (2-3), 249-275, 2007
1082007
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
852000
Sparse grids and applications
J Garcke, M Griebel
Springer Science & Business Media, 2012
662012
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
632013
Importance weighted inductive transfer learning for regression
J Garcke, T Vanck
Joint European conference on machine learning and knowledge discovery in …, 2014
572014
Maschinelles Lernen durch Funktionsrekonstruktion mit verallgemeinerten dünnen Gittern
J Garcke
Universitäts-und Landesbibliothek Bonn, 2004
572004
Classification with sparse grids using simplicial basis functions
J Garcke, M Griebel
Intelligent data analysis 6 (6), 483-502, 2002
502002
Regression with the optimised combination technique
J Garcke
Proceedings of the 23rd international conference on Machine learning, 321-328, 2006
472006
A dimension adaptive sparse grid combination technique for machine learning
J Garcke
Anziam Journal 48, C725-C740, 2006
452006
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
422017
Fitting multidimensional data using gradient penalties and the sparse grid combination technique
J Garcke, M Hegland
Computing 84 (1), 1-25, 2009
402009
Approximating Gaussian Processes with H^2-Matrices
S Börm, J Garcke
European Conference on Machine Learning, 42-53, 2007
352007
Combining machine learning and simulation to a hybrid modelling approach: Current and future directions
L von Rueden, S Mayer, R Sifa, C Bauckhage, J Garcke
International Symposium on Intelligent Data Analysis, 548-560, 2020
342020
On the numerical solution of the chemical master equation with sums of rank one tensors
M Hegland, J Garcke
ANZIAM Journal 52, C628-C643, 2010
312010
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