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In-Situ Machine Learning (ISML)

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/isml
https://doi.org/10.11578/dc.20220224.2

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Abstract

SAND2022-1478 O In-Situ Machine Learning (ISML) is a library of functions that can be combined to create algorithms for in-situ event detection. 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:
Shead, Timothy [1][2][3] ;  Davis IV, Warren [1][2][3] ;  Kolla, Hemanth [1][2][3] ;  Popoola, Gabriel [1][2][3] ;  Carlson, Max [1][2][3] ;  Tezaur, Irina [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:
2022-01-31
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python 3
Version:
1.0
Licenses:
Apache License 2.0
Sponsoring Org.:
Code ID:
70383
Site Accession Number:
SCR #2746
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States
Keywords:
SciDAC

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/isml
https://doi.org/10.11578/dc.20220224.2

SAVE / SHARE



SNL Badge
SciDAC Badge

Citation Formats

Shead, Timothy, Davis IV, Warren, Kolla, Hemanth, Popoola, Gabriel, Carlson, Max, and Tezaur, Irina. In-Situ Machine Learning (ISML). Computer Software. https://github.com/sandialabs/isml. USDOE. 31 Jan. 2022. Web. doi:10.11578/dc.20220224.2.
Shead, Timothy, Davis IV, Warren, Kolla, Hemanth, Popoola, Gabriel, Carlson, Max, & Tezaur, Irina. (2022, January 31). In-Situ Machine Learning (ISML). [Computer software]. https://github.com/sandialabs/isml. https://doi.org/10.11578/dc.20220224.2.
Shead, Timothy, Davis IV, Warren, Kolla, Hemanth, Popoola, Gabriel, Carlson, Max, and Tezaur, Irina. "In-Situ Machine Learning (ISML)." Computer software. January 31, 2022. https://github.com/sandialabs/isml. https://doi.org/10.11578/dc.20220224.2.
@misc{ doecode_70383,
title = {In-Situ Machine Learning (ISML)},
author = {Shead, Timothy and Davis IV, Warren and Kolla, Hemanth and Popoola, Gabriel and Carlson, Max and Tezaur, Irina},
abstractNote = {SAND2022-1478 O In-Situ Machine Learning (ISML) is a library of functions that can be combined to create algorithms for in-situ event detection. 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.20220224.2},
url = {https://doi.org/10.11578/dc.20220224.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20220224.2}},
year = {2022},
month = {jan}
}