ETH :: D-MATH :: Numerical Solution of PDEs with Stochastic Data

Participants in the seminar will read research papers on solution techniques for partial differential and integral equations with stochastic data. Goals are to show comprehension and ability for independent study of current research literature in numerical analysis and scientific computing results related to stochastic partial differential equations.

Material will cover: wavelet-based multiresolution methods for stochastic PDEs, polynomial chaos based stochastic Galerkin methods for stochastic PDEs.

Literatur

B. Oksendal, "Stochastic Differential Equations"

M. Loeve, "Probability theory"

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Talks

May, 9	Philipp Arbenz	Ito integrals	B. Oksendal, "Stochastic Differential Equations"
May, 30	Andreas Goelzer	The Ito formula and the martingale representation theorem	B. Oksendal, "Stochastic Differential Equations"
June, 6 June, 13	Bela Bauer Lars Bonnes	Karhunen-Loeve approximation Karhunen-Loeve approximation of random fields by generalized fast multipole methods	M. Loeve, "Probability theory II" Ch. Schwab, R.-A. Todor, J. Comp. Phys 217, 100--122

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