Schick, Michael Dr. rer. nat.Universität HeidelbergHeidelberg
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- John, David: Learning model discrepancy of an electric motor with Bayesian inference / David John, Michael Schick, Vincent Heuveline. -
Heidelberg: Univ.-Bibliothek, August 23, 2018. - 1 Online-Ressource (23 Seiten)
(Preprint series of the Engineering Mathematics and Computing Lab (EMCL) ; Preprint no. 2018-01)
DOI: 10.11588/emclpp.2018.1.51320
- Schick, Michael: A Newton-Galerkin method for fluid flow exhibiting uncertain periodic dynamics / M. Schick, V. Heuveline, O.P. Le Maître, 04 February 2016. - 22 S.
In: SIAM review, ISSN 1095-7200. 58(2016), 1, Seite 119-140
DOI: 10.1137/15M104311X
- Gerstner, Philipp: A domain decomposition approach for solving dynamic optimal power flow problems in parallel with application to the German transmission grid / Philipp Gerstner, Michael Schick, Vincent Heuveline, Nico Meyer-Hübner, Michael Suriyah, Thomas Leib… . -
Heidelberg: Univ.-Bibl., 2016. - Online-Ressource (25 Seiten)
(Preprint series of the Engineering Mathematics and Computing Lab (EMCL) ; 2016,1)
DOI: 10.11588/emclpp.2016.1.33784
- Gerstner, Philipp: A multilevel domain decomposition approach for solving time constrained optimal power flow problems / Philipp Gerstner, Vincent Heuveline, Michael Schick. -
Heidelberg: Univ.-Bibl., 2015. - Online-Ressource (30 S.)
(Preprint series of the Engineering Mathematics and Computing Lab (EMCL) ; 2015,4)
DOI: 10.11588/emclpp.2015.04.23517
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