180 citations · 319 across the 15 of their papers we have counts for
15 papers
Model Error Embedding with Orthogonal Gaussian Processes
Mridula Kuppa, Khachik Sargsyan, Marco Panesi +1
Computational models of complex physical systems often rely on simplifying assumptions which inevitably introduce model error, with consequent predictive errors. Given data on mode…
Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling
Haley Rosso, Lars Ruthotto, Khachik Sargsyan
Continuous-time deep learning models, such as neural ordinary differential equations (ODEs), offer a promising framework for surrogate modeling of complex physical systems. A centr…
Improving the quasi-biennial oscillation via a surrogate-accelerated multi-objective optimization
Luis Damiano, Walter M. Hannah, Chih-Chieh Chen +4
Simulating the QBO remains a formidable challenge partly due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantificat…
Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty
Joy N. Mueller, Khachik Sargsyan, Craig J. Daniels +1
Engineering and applied science rely on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and…
Bayesian calibration with summary statistics for the prediction of xenon diffusion in UO2 nuclear fuel
Pieterjan Robbe, David Andersson, Luc Bonnet +5
The evolution and release of fission gas impacts the performance of UO2 nuclear fuel. We have created a Bayesian framework to calibrate a novel model for fission gas transport that…
Global Sensitivity Analysis of a coupled multiphysics model to predict surface evolution in fusion plasma-surface interactions
Pieterjan Robbe, Sophie Blondel, Tiernan Casey +4
We construct a global sensitivity analysis framework for a coupled multiphysics model used to predict the changes in material properties and surface morphology of helium plasma-fac…