Dirk Pflüger
Dirk Pflüger
Verified email at ipvs.uni-stuttgart.de - Homepage
Cited by
Cited by
Spatially adaptive sparse grids for high-dimensional problems
DM Pflüger
Technische Universität München, 2010
Modellbildung und Simulation: eine anwendungsorientierte Einführung
HJ Bungartz, S Zimmer, M Buchholz, D Pflüger
Springer-Verlag, 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
Spatially adaptive refinement
D Pflüger
Sparse grids and applications, 243-262, 2012
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
Modeling and Simulation: An Application-Oriented Introduction
HJ Bungartz, S Zimmer, M Buchholz, D Pflüger
Optimization 53, 2014
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
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
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
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
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
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
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
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
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
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
Adaptive sparse grid techniques for data mining
HJ Bungartz, D Pflüger, S Zimmer
Modeling, simulation and optimization of complex processes, 121-130, 2008
Hierarchical gradient-based optimization with B-splines on sparse grids
J Valentin, D Pflüger
Sparse Grids and Applications-Stuttgart 2014, 315-336, 2016
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
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
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