270 citations · 318 across the 12 of their papers we have counts for
16 papers
Analytically Optimal Sample Allocations for Nested Multivariate Multifidelity Control Variate Estimators
Atticus Rex, Elizabeth Qian
Monte Carlo estimation, an essential tool for quantifying uncertainty in complex scientific and engineering applications, often has unacceptably large errors when computing resourc…
Sparse POD Mode Selection and Manifold Dimensionality Reduction with Neural Networks
Tomoki Koike, Prakash Mohan, Marc T. Henry de Frahan +2
Linear dimensionality reduction methods such as proper orthogonal decomposition (POD) make high-dimensional data amenable to analysis by identifying the principal components, or mo…
Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
Atticus Rex, Elizabeth Qian, David Peterson
Supervised machine learning describes the practice of fitting a parameterized model to labeled input-output data. Supervised machine learning methods have demonstrated promise in l…
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…
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…