270 citations · 318 across the 12 of their papers we have counts for
4 papers · 1 filter
Physics-Informed Machine Learning for Characterizing System Stability
Tomoki Koike, Elizabeth Qian
In the design and operation of complex dynamical systems, it is essential to ensure that all state trajectories of the dynamical system converge to a desired equilibrium within a g…
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…
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…
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…