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U.S. Department of Energy
Office of Scientific and Technical Information

Efficent XAI Information Saliency Tool

Software ·
DOI:https://doi.org/10.11578/dc.20200513.2· OSTI ID:code-35964 · Code ID:35964
 [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
This software is an implementation which is described in: "Efficient Saliency Maps for Explainable AI" (https://openreview.net/forum?id=ryxf9CEKDr). The toolkit is located in: https://mybitbucket.llnl.gov/projects/SAL/repos/smoe_lovi/browse. It is a set of of PyTorch related python scripts for extracting the what parts of an image are most salient to a deep neural network in an efficient manner. This source will allow one to replicate the results in the paper referenced above. Is there
Short Name / Acronym:
EXIST
Site Accession Number:
LLNL-CODE-802426
Software Type:
Scientific
License(s):
BSD 3-clause "New" or "Revised" License
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)

Primary Award/Contract Number:
AC52-07NA27344
DOE Contract Number:
AC52-07NA27344
Code ID:
35964
OSTI ID:
code-35964
Country of Origin:
United States

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