Numerical methods for SPDE

Wednesday, May 1st is a Bank holiday in Spain. The new schedule for this course is as follows:
April 29 ( 9-12h)
April 30 (9-11h)
May 1 (holiday)
May 2 (9-12h) 
May 3 (9-11h)

The course provides and introduction to numerical methods for the approximate solutions of partial differential equations that have random inputs, e.g., forcing functions, coefficients, boundary data, domain definition, etc. Both random field and random parameter type inputs are considered. The topics considered could include:
- Introductory remarks and definition of forward and inverse problems
- Approximation of white and colored random fields
- Stochastic Galerkin methods
- Spectral approximations
- Collocation approximations
- Sampling methods
- Surrogate approximation methods
- Sparse grid methods
- Local polynomial approximations
- Wavelet approximation methods
- Control, optimization, and identification problems
The course is oriented towards graduate students having a basic background in numerical analysis and with some familiarity with PDEs; the statistical and probabilistic aspects will be largely self contained.

GUNZBURGER2012-13

Gunzburger-Bcam-Spde-Sc.pdf

BCAMCOURSE2012-13GUNZBURGER

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