skip to content
 

Subspace-based dimension reduction for forward and inverse uncertainty quantification

Presented by: 
Paul Constantine University of Colorado
Date: 
Monday 9th April 2018 - 11:30 to 12:00
Venue: 
INI Seminar Room 1
Abstract: 
Many methods in uncertainty quantification suffer from the curse of dimensionality. I will discuss several approaches for identifying exploitable low-dimensional structure---e.g., active subspaces or likelihood-informed subspaces---that enable otherwise infeasible forward and inverse uncertainty quantification.

Related Links
The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons