Stochastic PDEs

SIAM J. Numer. Anal. - A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

1 min read · Sat, Jun 9 2007

Stochastic PDEs uncertainty quantification

In this paper, we propose and analyze a stochastic collocation method to solve elliptic partial differential equations with random coefficients and forcing terms (input data of the model). The input data are assumed to depend on a finite number of random variables.

Dr. A. Litvinenko together with colleagues from France and Germany is organizing a minisymposia at Congress on Industrial and Applied Mathematics (ICIAM2015), Aug. 10-14, 2015 in Beijing, China

1 min read · Mon, Aug 10 2015

Stochastic PDEs

Approximations of stochastic and multi-parametric differential equations may lead to extremely high dimensional problems that suffer from the so called curse of dimensionality. Computational tractability may be recovered by relying on adaptive low-rank/sparse approximation.