Muschalik, M., Fumagalli, F., Hammer, B., &; Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence, 38(13), 14388–14396.https://doi.org/10.1609/aaai.v38i13.29352 

Muschalik, M., Fumagalli, F., Hammer, B., &; Huellermeier, E. (2023). iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. In Machine Learning and Knowledge Discovery in Databases: Research Track. Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-43418-1_26 

Muschalik, M., Fumagalli, F., Jagtani, R., Hammer, B., &; Huellermeier, E. (2023). iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. In Communications in Computer and Information Science. Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-44064-9_11 

Fumagalli, F., Muschalik, M., Hüllermeier, E., &; Hammer, B. (2023). On Feature Removal for Explainability in Dynamic Environments. ESANN 2023 Proceedings. ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online.https://doi.org/10.14428/esann/2023.es2023-148 

Fumagalli, F., Muschalik, M., Kolpaczki, P., Hüllermeier, E., &; Hammer, B. (2023). SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS 2023 - Advances in Neural Information Processing Systems, 36, 11515--11551.

Muschalik, M., Fumagalli, F., Hammer, B., &; Huellermeier, E. (2022). Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz, 36(3–4), 211–224.https://doi.org/10.1007/s13218-022-00766-6