Derivative-based global sensitivity analysis for models with high-dimensional inputs and functional outputs
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2019-02-17
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Helen L. Cleaves, Alen Alexanderian, Hayley Guy, Ralph C. Smith and Meilin Yu, Derivative-based global sensitivity analysis for models with high-dimensional inputs and functional outputs, 2019, https://arxiv.org/pdf/1902.04630.pdf
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Abstract
We present a framework for derivative-based global sensitivity analysis (GSA) for
models with high-dimensional input parameters and functional outputs. We combine ideas from
derivative-based GSA, random eld representation via Karhunen-Loeve expansions, and adjoint-
based gradient computation to provide a scalable computational framework for computing the pro-
posed derivative-based GSA measures. We illustrate the strategy for a nonlinear ODE model of
cholera epidemics and for elliptic PDEs with application examples from geosciences and biotrans-
port