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Michael Schick
Michael Schick
Bosch Research
Verified email at de.bosch.com
Title
Cited by
Cited by
Year
HiFlow3 a flexible and hardware-aware parallel finite element package
V Heuveline
Proceedings of the 9th Workshop on Parallel/High-Performance Object-Oriented …, 2010
482010
A hybrid generalized polynomial chaos method for stochastic dynamical systems
V Heuveline, M Schick
International Journal for Uncertainty Quantification 4 (1), 2014
302014
HiFlow3: A Hardware-Aware Parallel Finite Element Package
H Anzt, W Augustin, M Baumann, T Gengenbach, T Hahn, ...
Tools for High Performance Computing 2011: Proceedings of the 5th …, 2012
262012
Regionalizing input data for generation and transmission expansion planning models
V Slednev, M Ruppert, V Bertsch, W Fichtner, N Meyer-Hübner, M Suriyah, ...
Advances in Energy System Optimization: Proceedings of the first …, 2017
142017
A domain decomposition approach for solving dynamic optimal power flow problems in parallel with application to the German transmission grid
P Gerstner, M Schick, V Heuveline, N Meyer-Hübner, M Suriyah, ...
Preprint Series of the Engineering Mathematics and Computing Lab, 2016
122016
A Newton--Galerkin method for fluid flow exhibiting uncertain periodic dynamics
M Schick, V Heuveline, OP Le Ma
SIAM/ASA Journal on Uncertainty Quantification 2 (1), 153-173, 2014
122014
A local time--dependent Generalized Polynomial Chaos method for Stochastic Dynamical Systems
V Heuveline, M Schick
Preprint Series of the Engineering Mathematics and Computing Lab, 2011
122011
Comparison between a polynomial chaos surrogate model and Markov Chain Monte Carlo for inverse uncertainty quantification based on an electric drive test bench
P Glaser, M Schick, K Petridis, V Heuveline
ECCOMAS Congress 2016, 2016
112016
New developments in modeling network constraints in techno-economic energy system expansion planning models
M Schönfelder, A Eßer-Frey, M Schick, W Fichtner, V Heuveline, ...
Zeitschrift für Energiewirtschaft 1 (36), 27-35, 2012
102012
Time constrained optimal power flow calculations on the German power grid
N Meyer-Hübner, MR Suriyah, T Leibfried, V Slednev, V Bertsch, ...
International ETG Congress 2015; Die Energiewende-Blueprints for the new …, 2015
92015
Uncertainty quantification for stochastic dynamical systems: Spectral methods using generalized polynomial chaos
M Schick
Karlsruhe, Karlsruher Institut für Technologie (KIT), Diss., 2011, 2012
82012
Towards a hybrid numerical method using generalized polynomial chaos for stochastic differential equations
V Heuveline, M Schick
Preprint Series of the Engineering Mathematics and Computing Lab, 2011
62011
Learning model discrepancy of an electric motor with Bayesian inference
DN John, M Schick, V Heuveline
Multidisciplinary Digital Publishing Institute Proceedings 33 (1), 11, 2019
52019
Optimal storage operation with model predictive control in the German transmission grid
N Meyer-Hübner, M Suriyah, T Leibfried, V Slednev, V Bertsch, W Fichtner, ...
Advances in Energy System Optimization: Proceedings of the first …, 2017
42017
Uncertainty quantification and high performance computing (dagstuhl seminar 16372)
V Heuveline, M Schick, C Webster, P Zaspel
Schloss-Dagstuhl-Leibniz Zentrum für Informatik, 2017
42017
A Newton--Galerkin Method for Fluid Flow Exhibiting Uncertain Periodic Dynamics
M Schick, V Heuveline, OP Le Ma
siam REVIEW 58 (1), 119-140, 2016
42016
A Polynomial Chaos Method for Uncertainty Quantification in blood pump simulation
M Schick, C Song, V Heuveline
National Technical University of Athens, 93-106, 2015
42015
A parallel multilevel spectral galerkin solver for linear systems with uncertain parameters
M Schick
2014 22nd Euromicro International Conference on Parallel, Distributed, and …, 2014
42014
Hierarchical surrogate-based Approximate Bayesian Computation for an electric motor test bench
DN John, L Stohrer, C Schillings, M Schick, V Heuveline
arXiv preprint arXiv:2106.09597, 2021
32021
Modeling of a likelihood function based on a global sensitivity analysis
P Glaser, P Kosmas, M Schick, V Heuveline
PAMM 17 (1), 719-720, 2017
32017
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