DOE OSTI · code-125566
Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning
Abstract
This repository contains python scripts and numerical data accompanying the paper: "Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning," Tyler Chang, Andrew Gillette, Romit Maulik, 2024. The following subdirectories are included: - "interpolants" contains our interpolation scripts used for all studies - "experiments" contains scripts demonstrating our experiments with synthetic data - "airfoil" contains scripts demonstrating our experiments with the publicly available UIUC airfoil dataset. Further instructions are provided in READMEs within the sub-directories.
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Gillette, Andrew, Maulik, Romit, Chang, Tyler. 2024-02-23. Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning. https://doi.org/10.11578/dc.20240401.2
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