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.
- Developers:
-
Gillette, Andrew [1] ; Maulik, Romit [2] ; Chang, Tyler [2]
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Argonne National Lab., Idaho Falls, ID (United States)
- Release Date:
- 2024-02-23
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Version:
- 1.0
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOE National Nuclear Security Administration (NNSA)Primary Award/Contract Number:AC52-07NA27344
- Code ID:
- 125566
- Site Accession Number:
- LLNL-CODE-862386
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Country of Origin:
- United States
Citation Formats
Gillette, Andrew, Maulik, Romit, and Chang, Tyler.
Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning.
Computer Software.
https://github.com/LLNL/interpML.
USDOE National Nuclear Security Administration (NNSA).
23 Feb. 2024.
Web.
doi:10.11578/dc.20240401.2.
Gillette, Andrew, Maulik, Romit, & Chang, Tyler.
(2024, February 23).
Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning.
[Computer software].
https://github.com/LLNL/interpML.
https://doi.org/10.11578/dc.20240401.2.
Gillette, Andrew, Maulik, Romit, and Chang, Tyler.
"Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning." Computer software.
February 23, 2024.
https://github.com/LLNL/interpML.
https://doi.org/10.11578/dc.20240401.2.
@misc{
doecode_125566,
title = {Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning},
author = {Gillette, Andrew and Maulik, Romit and Chang, Tyler},
abstractNote = {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.},
doi = {10.11578/dc.20240401.2},
url = {https://doi.org/10.11578/dc.20240401.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240401.2}},
year = {2024},
month = {feb}
}