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07/05/2023
Conditional Korhunen-Loéve regression model with Basis Adaptation for high-dimensional problems: uncertainty quantification and inverse modeling
We propose a methodology for improving the accuracy of surrogate models ...
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01/26/2023
Gaussian process regression and conditional Karhunen-Loéve models for data assimilation in inverse problems
We present a model inversion algorithm, CKLEMAP, for data assimilation a...
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07/30/2021
Physics-Informed Machine Learning Method for Large-Scale Data Assimilation Problems
We develop a physics-informed machine learning approach for large-scale ...
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12/16/2019
A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure
In this work, cascading transmission line failures are studied through a...
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04/17/2019
Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models
We use a conditional Karhunen-Loève (KL) model to quantify and reduce un...
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02/18/2019
Approximate Bayesian Model Inversion for PDEs with Heterogeneous and State-Dependent Coefficients
We present two approximate Bayesian inference methods for parameter esti...
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04/17/2018