5 papers · 1 filter
Likelihood-informed Model Reduction for Bayesian Inference of Static Structural Loads
Jakob Scheffels, Elizabeth Qian, Iason Papaioannou +1
Bayesian inverse problems use data to update a prior probability distribution on uncertain parameter values to a posterior distribution. Such problems arise in many structural engi…
Dimension and model reduction approaches for linear Bayesian inverse problems with rank-deficient prior covariances
Josie König, Elizabeth Qian, Melina A. Freitag
Bayesian inverse problems use observed data to update a prior probability distribution for an unknown state or parameter of a scientific system to a posterior distribution conditio…
Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems
Tomoki Koike, Prakash Mohan, Marc T. Henry de Frahan +2
Projection-based model reduction enables efficient simulation of complex dynamical systems by constructing low-dimensional surrogate models from high-dimensional data. The Operator…
An ensemble Kalman approach to randomized maximum likelihood estimation
Pavlos Stavrinides, Elizabeth Qian
This work proposes ensemble Kalman randomized maximum likelihood estimation, a new derivative-free method for performing randomized maximum likelihood estimation, which is a method…
The Fundamental Subspaces of Ensemble Kalman Inversion
Elizabeth Qian, Christopher Beattie
Ensemble Kalman Inversion (EKI) methods are a family of iterative methods for solving weighted least-squares problems, especially those arising in scientific and engineering invers…