Welcome to XpertAI! We believe that explainable artificial intelligence (XAI) is crucial for the informed application of machine learning methods in practice.
🎉 Our paper won the Best Paper Award at the 2025 World Conference on eXplainable Artificial Intelligence
(09–11 July, 2025 — Istanbul, Turkey) 🎉
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.pyto help you faithfully explain your own models.
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}
}