This repository is a supplement to the following paper:

Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek. Efficient and Accurate Explanation Estimation with Distribution Compression. ICLR 2025 (Spotlight)

In examples, we provide 4 Jupyter notebooks with simple code examples on how to use CTE to improve the estimation of SHAP, SAGE, Expected Gradients, and Feature Effects.

In experiments, we provide code to reproduce the results reported in Section 4 of the paper.

@inproceedings{baniecki2025efficient,
    title     = {Efficient and Accurate Explanation Estimation with Distribution Compression},
    author    = {Hubert Baniecki and 
                 Giuseppe Casalicchio and 
                 Bernd Bischl and 
                 Przemyslaw Biecek},
    booktitle = {International Conference on Learning Representations},
    year      = {2025},
    url       = {https://openreview.net/forum?id=LiUfN9h0Lx}
}

This work was financially supported by the Polish National Science Centre grant number 2021/43/O/ST6/00347. Hubert Baniecki gratefully acknowledges scholarship funding from the Polish National Agency for Academic Exchange under the Preludium Bis NAWA 3 programme.