Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles

Muschalik M, Fumagalli F, Hammer B, Hüllermeier E (2024)
Proceedings of the AAAI Conference on Artificial Intelligence 38(13): 14388-14396.

SHAP-IQ: Unified Approximation of any-order Shapley Interactions

Fumagalli F, Muschalik M, Kolpaczki P, Hüllermeier E, Hammer B (2023)
In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023).

On Feature Removal for Explainability in Dynamic Environments

Fumagalli F, Muschalik M, Hüllermeier E, Hammer B (2023)
In: ESANN 2023 proceedings. 83-88.

iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams

Muschalik M, Fumagalli F, Hammer B, Hüllermeier E (2023)
In: Machine Learning and Knowledge Discovery in Databases: Research Track. European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part III. Koutra D, Plant C, Gomez Rodriguez M, Baralis E, Bonchi F (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 428-445.

Incremental permutation feature importance (iPFI): towards online explanations on data streams

Fumagalli F, Muschalik M, Hüllermeier E, Hammer B (2023)
Machine Learning .

iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios

Muschalik M, Fumagalli F, Jagtani R, Hammer B, Hüllermeier E (2023)
In: Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part I. Longo L (Ed); Communications in Computer and Information Science. Cham: Springer Nature Switzerland: 177-194.

Agnostic Explanation of Model Change based on Feature Importance

Muschalik M, Fumagalli F, Hammer B, Hüllermeier E (2022)
KI - Künstliche Intelligenz.