scio-pypi 1.0.0

Statistical Confidence from Internal Observations

scio

Confidence scores for Neural Networks, made easy!

“scio me nihil scire”

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# Install from PyPI
pip install scio-pypi

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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.