XpertAI 🚀

Welcome to XpertAI! We believe that explainable artificial intelligence (XAI) is crucial for the informed application of machine learning methods in practice.

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📰 News

🎉 Our paper won the Best Paper Award at the 2025 World Conference on eXplainable Artificial Intelligence
(09–11 July, 2025 — Istanbul, Turkey) 🎉

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📖 About

This repository contains the supplementary code for our paper:
"XpertAI: Uncovering Regression Model Strategies for Sub-manifolds"

You’ll find:

• A tutorial notebook demonstrating the wine-quality prediction example from the paper.
• Helper functions in utils.py to help you faithfully explain your own models.

Cite

In case you utilize the published code for your own paper, please cite us accordingly:

@incollection{XpertAI2025,
  author       = {Letzgus, S. and Müller, K. R. and Montavon, G.},
  title        = {XpertAI: Uncovering Regression Model Strategies for Sub-manifolds},
  booktitle    = {Explainable Artificial Intelligence. xAI 2025},
  editor       = {Guidotti, R. and Schmid, U. and Longo, L.},
  series       = {Communications in Computer and Information Science},
  volume       = {2578},
  publisher    = {Springer},
  address      = {Cham},
  year         = {2026},
  doi          = {10.1007/978-3-032-08327-2_19},
  url          = {https://doi.org/10.1007/978-3-032-08327-2_19}
}