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GP-BayesOpInf

McQuarrie, Shane·Chaudhuri, Anirban·Willcox, Karen·Guo, Mengwu
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Abstract

SAND2025-01851O GP-BayesOpInf is a software tool that uses algorithms to combine Gaussian process regression, principal component analysis, and linear Bayesian inference to produce a probabilistic reduced-order model for time-dependent systems. Numerical examples include the compressible Euler equations for an ideal gas, a heat diffusion process with a nonlinear reaction term, and a set of ordinary differential equations describing a compartmental model in epidemiology. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

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McQuarrie, Shane, Chaudhuri, Anirban, Willcox, Karen, Guo, Mengwu. 2024-09-12. GP-BayesOpInf. https://doi.org/10.11578/dc.20250909.16

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