1 citations · 1 across the 1 of their papers we have counts for
6 papers
Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes
Grace Guinan, Michelle A. Smeaton, Brian C. Wyatt +6
Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-lay…
A Lanczos-Stieltjes method for one-dimensional ridge function approximation and integration
Andrew Glaws, Paul G. Constantine
Many of the input-parameter-to-output-quantity-of-interest maps that arise in computational science admit a surprising low-dimensional structure, where the outputs vary primarily a…
Inverse regression for ridge recovery II: Numerics
Andrew Glaws, Paul G. Constantine, R. Dennis Cook
We investigate the application of sufficient dimension reduction (SDR) to a noiseless data set derived from a deterministic function of several variables. In this context, SDR prov…
Gauss-Christoffel quadrature for inverse regression: applications to computer experiments
Andrew Glaws, Paul G. Constantine
Sufficient dimension reduction (SDR) provides a framework for reducing the predictor space dimension in regression problems. We consider SDR in the context of deterministic functio…
Inverse regression for ridge recovery: A data-driven approach for parameter reduction in computer experiments
Andrew T. Glaws, Paul G. Constantine, R. Dennis Cook
Parameter reduction can enable otherwise infeasible design and uncertainty studies with modern computational science models that contain several input parameters. In statistical re…
Dimension reduction in MHD power generation models: dimensional analysis and active subspaces
Andrew Glaws, Paul G. Constantine, John Shadid +1
Magnetohydrodynamics (MHD)---the study of electrically conducting fluids---can be harnessed to produce efficient, low-emissions power generation. Today, computational modeling assi…