Lehrinhalte
Monte Carlo finite elements, multi level Monte Carlo finite elements, Karhunen Loeve expansion of random fields, stochastic Galerkin methods: formulation, implementation, solution and error estimation, stochastic collocation
Literatur
G. J. Lord, C. E. Powell, and T. Shardlow. An Introduction to Computational Stochastic PDEs. Cambridge University Press, 2014.
R. C. Smith. Uncertainty Quantification: Theory, Implementation, and Applications. SIAM Computational Science and Engineering, 2014.
D. Xiu. Numerical Methods for Stochastic Computations: A Spectral Method Approach. Princeton University Press, 2010.
Voraussetzungen
recommended: Introduction to Numerical Analysis, Introduction to Stochastics
ideally: Numerical Analysis of Partial Differential Equations
Monte Carlo finite elements, multi level Monte Carlo finite elements, Karhunen Loeve expansion of random fields, stochastic Galerkin methods: formulation, implementation, solution and error estimation, stochastic collocation
Literatur
G. J. Lord, C. E. Powell, and T. Shardlow. An Introduction to Computational Stochastic PDEs. Cambridge University Press, 2014.
R. C. Smith. Uncertainty Quantification: Theory, Implementation, and Applications. SIAM Computational Science and Engineering, 2014.
D. Xiu. Numerical Methods for Stochastic Computations: A Spectral Method Approach. Princeton University Press, 2010.
Voraussetzungen
recommended: Introduction to Numerical Analysis, Introduction to Stochastics
ideally: Numerical Analysis of Partial Differential Equations
- Lehrende: Jens Lang
- Lehrende: Hendrik Wilka
Semester: ST 2020