Statistical Confidence from Internal Observations
Project description
scio
Confidence scores for Neural Networks, made easy!
“scio me nihil scire”
# Install from PyPI
pip install scio-pypi
Demo 🎮
Documentation 📖
The full documentation can be found here. You may learn more about scio, get started and follow tutorials, or specifically browse API references and scientific literature references.
Citing scio 🎓
If our library contributed to your research or project, please consider citing it. For convenience, we provide the following BibTeX entry for the entire code base.
@software{ThalesGroup/scio,
title = {scio: {C}onfidence scores for {N}eural {N}etworks, made easy!},
author = {Élie Goudout and the scio community},
url = {github.com/ThalesGroup/scio},
doi = {10.5281/zenodo.17160013},
year = {2025}
}
To reference a particular release, get the DOI here.
Contributing 💫
Questions, issues, discussions and pull requests are welcome! Read our contributing guide and join our team of contributors ✨
For development, we recommend using uv since we ship uv.lock for better development reproducibility.
Star history ⭐
License ⚖️
This package is distributed under the MIT license. The use of NVIDIA proprietary modules (for GPU acceleration) is optional.
Release history Release notifications | RSS feed
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