Abstract
SAND2022-6885 O Minima-Preserving Neural Network (MPNN) is a software library for learning functions with known minima location. 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:
-
Sargsyan, Khachik [1][2][3]
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Release Date:
- 2022-04-04
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Python
- Version:
- 1.0
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:NA0003525
- Code ID:
- 94667
- Site Accession Number:
- SCR #2771
- Research Org.:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Country of Origin:
- United States
Citation Formats
Sargsyan, Khachik.
MPNN.
Computer Software.
https://github.com/sandialabs/MPNN.
USDOE.
04 Apr. 2022.
Web.
doi:10.11578/dc.20221010.2.
Sargsyan, Khachik.
(2022, April 04).
MPNN.
[Computer software].
https://github.com/sandialabs/MPNN.
https://doi.org/10.11578/dc.20221010.2.
Sargsyan, Khachik.
"MPNN." Computer software.
April 04, 2022.
https://github.com/sandialabs/MPNN.
https://doi.org/10.11578/dc.20221010.2.
@misc{
doecode_94667,
title = {MPNN},
author = {Sargsyan, Khachik},
abstractNote = {SAND2022-6885 O Minima-Preserving Neural Network (MPNN) is a software library for learning functions with known minima location. 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.20221010.2},
url = {https://doi.org/10.11578/dc.20221010.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20221010.2}},
year = {2022},
month = {apr}
}