41 citations · 198 across the 24 of their papers we have counts for
4 papers · 1 filter
Multifidelity Dimension Reduction via Active Subspaces
Rémi Lam, Olivier Zahm, Youssef Marzouk +1
We propose a multifidelity dimension reduction method to identify a low-dimensional structure present in many engineering models. The structure of interest arises when functions va…
Randomized residual-based error estimators for parametrized equations
Kathrin Smetana, Olivier Zahm, Anthony T Patera
We propose a randomized a posteriori error estimator for reduced order approximations of parametrized (partial) differential equations. The error estimator has several important pr…
Certified dimension reduction in nonlinear Bayesian inverse problems
Olivier Zahm, Tiangang Cui, Kody Law +2
We propose a dimension reduction technique for Bayesian inverse problems with nonlinear forward operators, non-Gaussian priors, and non-Gaussian observation noise. The likelihood f…
Gradient-based dimension reduction of multivariate vector-valued functions
Olivier Zahm, Paul Constantine, Clémentine Prieur +1
Multivariate functions encountered in high-dimensional uncertainty quantification problems often vary most strongly along a few dominant directions in the input parameter space. We…