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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.

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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons