An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Projects: pypi: tf-explain

https://packages.ecosyste.ms/registries/pypi.org/packages/tf-explain

Interpretability Callbacks for Tensorflow 2.0
7 versions
Latest release: over 3 years ago
5 dependent packages
1,957 downloads last month

Enhanced Analysis
Repository Activity:
Repository Owner: Sicara (organization)
README Analysis: ArXiv Preprint CITATION.cff
Science Score: 61/100
Starting Score: 100 points
Bonuses:
  • +10 Science terms in README
    5 scientific terms found in README
  • +6 Academic links
    1 academic links found in README
  • +15 CITATION.cff file
    Contains citation file for academic attribution
Penalties:
  • -10 PyPI ecosystem
    General-purpose ecosystem
  • -15 No science keywords
    No scientific terms found in keywords/classifiers
  • -10 No science terms in description
    No scientific terms found in description
  • -25 Non-science indicators
    1 non-scientific terms found

Very Likely Science (61)

Papers Mentioning tf-explain 4

10.3390/cancers13102419
Deep Learning for the Classification of Non-Hodgkin Lymphoma on Histopathological Images
Cited by: 16
Author(s): Georg Steinbuß, Mark Kriegsmann, Christiane Zgorzelski, Alexander Brobeil, Benjamin Goeppert, Sascha Dietrich, Gunhild Mechtersheimer, Katharina Kriegsmann
Software Mentions: 18
Published: about 4 years ago
10.3390/ijms22105385
Deep Learning in Pancreatic Tissue: Identification of Anatomical Structures, Pancreatic Intraepithelial Neoplasia, and Ductal Adenocarcinoma
Cited by: 15
Author(s): Mark Kriegsmann, Katharina Kriegsmann, Georg Steinbuß, Christiane Zgorzelski, Anne Kraft, Matthias M. Gaida
Software Mentions: 18
Published: about 4 years ago
10.3389/fpsyt.2020.551299
Illuminating the Black Box: Interpreting Deep Neural Network Models for Psychiatric Research
Cited by: 32
Author(s): Yi-han Sheu
Software Mentions: 3
Published: over 4 years ago
10.1038/s41598-021-89225-0
Understanding inherent image features in CNN-based assessment of diabetic retinopathy
Cited by: 21
Author(s): Roc Reguant, Søren Brunak, Sajib Saha
Software Mentions: 1
Published: about 4 years ago