| Springer International Publishing: Cham BA Schulte, TE Goodwin, MH Ferkin Switzerland, 2016 | 405 | 2016 |
| Spatially adaptive sparse grids for high-dimensional problems DM Pflüger Technische Universität München, 2010 | 270 | 2010 |
| Modeling and Simulation: An Application-Oriented Introduction HJ Bungartz, S Zimmer, M Buchholz, D Pflüger Optimization 53, 2014 | 222* | 2014 |
| Modellbildung und Simulation: eine anwendungsorientierte Einführung HJ Bungartz, S Zimmer, M Buchholz, D Pflüger Springer-Verlag, 2009 | 210 | 2009 |
| Pdebench: An extensive benchmark for scientific machine learning M Takamoto, T Praditia, R Leiteritz, D MacKinlay, F Alesiani, D Pflüger, ... Advances in Neural Information Processing Systems 35, 1596-1611, 2022 | 119 | 2022 |
| Spatially adaptive sparse grids for high-dimensional data-driven problems D Pflüger, B Peherstorfer, HJ Bungartz Journal of Complexity 26 (5), 508-522, 2010 | 101 | 2010 |
| 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 | 88 | 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 | 50 | 2014 |
| Spatially adaptive refinement D Pflüger Sparse grids and applications, 243-262, 2012 | 50 | 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 | 44 | 2012 |
| Extending a Highly Parallel Data Mining Algorithm to the Intel ® Many Integrated Core Architecture A Heinecke, M Klemm, D Pflüger, A Bode, HJ Bungartz Euro-Par 2011: Parallel Processing Workshops: CCPI, CGWS, HeteroPar, HiBB …, 2012 | 42 | 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 | 40 | 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 | 34 | 2011 |
| Evaluation of pool-based testing approaches to enable population-wide screening for COVID-19 T de Wolff, D Pflüger, M Rehme, J Heuer, MI Bittner PLoS One 15 (12), e0243692, 2020 | 33 | 2020 |
| 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, 339-354, 2019 | 33 | 2019 |
| Hierarchical gradient-based optimization with B-splines on sparse grids J Valentin, D Pflüger Sparse Grids and Applications-Stuttgart 2014, 315-336, 2016 | 32 | 2016 |
| 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 |
| From piz daint to the stars: simulation of stellar mergers using high-level abstractions G Daiß, P Amini, J Biddiscombe, P Diehl, J Frank, K Huck, H Kaiser, ... Proceedings of the International Conference for High Performance Computing …, 2019 | 31 | 2019 |
| 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 | 30 | 2013 |
| 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 | 29 | 2012 |
Mario HeeneUniversity of Stuttgart在 ipvs.uni-stuttgart.de 的电子邮件经过验证
