High dimensional sparse polynomial approximation of parametric PDE's

  • Albert Cohen (Université Pierre et Marie Curie, Paris, France)
Felix-Klein-Hörsaal Universität Leipzig (Leipzig)


Various mathematical problems are challenged by the fact they involve functions of a very large number of variables. Such problems arise naturally in learning theory, partial differential equations or numerical models depending on parametric or stochastic variables. They typically result in numerical difficulties due to the so-called ''curse of dimensionality''. We shall explain how these difficulties may be handled in the context of stochastic-parametric PDE's based on the concept of sparse polynomial approximation.

10/28/13 10/30/13

Numerical Analysis and Scientific Computing

Universität Leipzig Felix-Klein-Hörsaal

Katja Heid

Jörg Lehnert

Jürgen Jost

Max-Planck-Institut für Mathematik in den Naturwissenschaften

Felix Otto

Max-Planck-Institut für Mathematik in den Naturwissenschaften

Harry Yserentant

Technische Universität Berlin