| Spatially adaptive sparse grids for high-dimensional problems DM Pflüger Technische Universität München, 2010 | 236 | 2010 |
| Modellbildung und Simulation: eine anwendungsorientierte Einführung HJ Bungartz, S Zimmer, M Buchholz, D Pflüger Springer-Verlag, 2009 | 180 | 2009 |
| Spatially adaptive sparse grids for high-dimensional data-driven problems D Pflüger, B Peherstorfer, HJ Bungartz Journal of Complexity 26 (5), 508-522, 2010 | 90 | 2010 |
| Modeling and Simulation: An Application-Oriented Introduction HJ Bungartz, S Zimmer, M Buchholz, D Pflüger Optimization 53, 2014 | 59 | 2014 |
| Polynomial chaos expansions for dependent random variables JD Jakeman, F Franzelin, A Narayan, M Eldred, D Pflüger Computer Methods in Applied Mechanics and Engineering 351, 643-666, 2019 | 50 | 2019 |
| Density estimation with adaptive sparse grids for large data sets B Peherstorfer, D Pflüger, HJ Bungartz Proceedings of the 2014 SIAM International Conference on Data Mining, 443-451, 2014 | 46 | 2014 |
| Spatially adaptive refinement D Pflüger Sparse grids and applications, 243-262, 2012 | 45 | 2012 |
| Option pricing with a direct adaptive sparse grid approach HJ Bungartz, A Heinecke, D Pflüger, S Schraufstetter Journal of Computational and Applied Mathematics 236 (15), 3741-3750, 2012 | 39 | 2012 |
| Compact data structure and scalable algorithms for the sparse grid technique A Murarasu, J Weidendorfer, G Buse, D Butnaru, D Pflüger ACM SIGPLAN Notices 46 (8), 25-34, 2011 | 37* | 2011 |
| Extending a Highly Parallel Data Mining Algorithm to the Intel ® Many Integrated Core Architecture A Heinecke, M Klemm, D Pflüger, A Bode, HJ Bungartz European Conference on Parallel Processing, 375-384, 2011 | 36 | 2011 |
| Multi-and many-core data mining with adaptive sparse grids A Heinecke, D Pflüger Proceedings of the 8th ACM International Conference on Computing Frontiers, 1-10, 2011 | 33 | 2011 |
| Load balancing for massively parallel computations with the sparse grid combination technique M Heene, C Kowitz, D Pflüger Parallel Computing: Accelerating Computational Science and Engineering (CSE …, 2014 | 32 | 2014 |
| Emerging architectures enable to boost massively parallel data mining using adaptive sparse grids A Heinecke, D Pflüger International Journal of Parallel Programming 41 (3), 357-399, 2013 | 29 | 2013 |
| Hierarchical gradient-based optimization with B-splines on sparse grids J Valentin, D Pflüger Sparse Grids and Applications-Stuttgart 2014, 315-336, 2016 | 26 | 2016 |
| Harnessing billions of tasks for a scalable portable hydrodynamic simulation of the merger of two stars T Heller, BA Lelbach, KA Huck, J Biddiscombe, P Grubel, AE Koniges, ... The International Journal of High Performance Computing Applications 33 (4 …, 2019 | 25 | 2019 |
| Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario M Köppel, F Franzelin, I Kröker, S Oladyshkin, G Santin, D Wittwar, ... Computational Geosciences 23 (2), 339-354, 2019 | 25 | 2019 |
| Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations F Franzelin, P Diehl, D Pflüger Meshfree methods for partial differential equations VII, 115-143, 2015 | 25 | 2015 |
| The combination technique for the initial value problem in linear gyrokinetics C Kowitz, D Pflüger, F Jenko, M Hegland Sparse Grids and Applications, 205-222, 2012 | 25 | 2012 |
| Towards a fault-tolerant, scalable implementation of GENE AP Hinojosa, C Kowitz, M Heene, D Pflüger, HJ Bungartz Recent Trends in Computational Engineering-CE2014, 47-65, 2015 | 24 | 2015 |
| Hybrid parallel solutions of the Black-Scholes PDE with the truncated combination technique J Benk, D Pflüger 2012 International Conference on High Performance Computing & Simulation …, 2012 | 24 | 2012 |
Mario HeeneUniversity of StuttgartVerified email at ipvs.uni-stuttgart.de
