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Conjugate gradient methods for stochastic Galerkin finite element matrices with saddle point structure

Müller, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
Conjugate gradient methods for stochastic Galerkin finite element matrices with saddle point structure.
In: Quantification of Uncertainty: Improving Efficiency and Technology (QUIET), Triest, Italy, 18.-21.07.2017, [Conference or Workshop Item]

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Müller, Christopher and Ullmann, Sebastian and Lang, Jens
Title: Conjugate gradient methods for stochastic Galerkin finite element matrices with saddle point structure
Language: English
Divisions: Exzellenzinitiative
Exzellenzinitiative > Graduate Schools
Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE)
04 Department of Mathematics
04 Department of Mathematics > Numerical Analysis and Scientific Computing
Event Title: Quantification of Uncertainty: Improving Efficiency and Technology (QUIET)
Event Location: Triest, Italy
Event Dates: 18.-21.07.2017
Date Deposited: 21 Aug 2017 07:13
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