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Confronting Domain Shift in Trained Neural Networks

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/confronting_domain_shift
https://doi.org/10.11578/dc.20240909.3

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Abstract

SAND2021-15138 O This code accompanies a paper published in the Proceedings of Machine Learning Research (PMLR), “Confronting Domain Shift in Trained Neural Networks.” 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.
Developers:
Martinez, Carianne [1][2][3]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Release Date:
2021-12-14
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Version:
1
Licenses:
MIT License
Sponsoring Org.:
Code ID:
94297
Site Accession Number:
SCR #2721
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/confronting_domain_shift
https://doi.org/10.11578/dc.20240909.3

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Citation Formats

Martinez, Carianne. Confronting Domain Shift in Trained Neural Networks. Computer Software. https://github.com/sandialabs/confronting_domain_shift. USDOE. 14 Dec. 2021. Web. doi:10.11578/dc.20240909.3.
Martinez, Carianne. (2021, December 14). Confronting Domain Shift in Trained Neural Networks. [Computer software]. https://github.com/sandialabs/confronting_domain_shift. https://doi.org/10.11578/dc.20240909.3.
Martinez, Carianne. "Confronting Domain Shift in Trained Neural Networks." Computer software. December 14, 2021. https://github.com/sandialabs/confronting_domain_shift. https://doi.org/10.11578/dc.20240909.3.
@misc{ doecode_94297,
title = {Confronting Domain Shift in Trained Neural Networks},
author = {Martinez, Carianne},
abstractNote = {SAND2021-15138 O This code accompanies a paper published in the Proceedings of Machine Learning Research (PMLR), “Confronting Domain Shift in Trained Neural Networks.” 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.},
doi = {10.11578/dc.20240909.3},
url = {https://doi.org/10.11578/dc.20240909.3},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240909.3}},
year = {2021},
month = {dec}
}