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Maragno, D., Röber, T. E., Kurtz, J., Goedhart, R., Birbil, S. I., & den Hertog, D. (in press). Finding regions of counterfactual explanations via robust optimization. INFORMS Journal on Computing.
2023
Cina, G., Röber, T. E., Goedhart, R., & Birbil, S. I. (2023). Semantic match: Debugging feature attribution methods in XAI for healthcare. In Proceedings of Machine Learning Research (Vol. 209, pp. 182-190)
2022
Lumadjeng, A. C., Röber, T. E., Akyuz, H., & Birbil, S. I. (2022). Rule Generation for Classification: Scalability, Interpretability, and Fairness. Manuscript submitted for publication.
Maragno, D., Röber, T. E., & Birbil, S. İ. (2022). Counterfactual Explanations Using Optimization With Constraint Learning. In OPT2022: Optimization for Machine Learning. Accepted papers OPT-ML. https://doi.org/10.48550/arXiv.2209.10997[details]
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