| SHAP-IQ: Unified approximation of any-order shapley interactions F Fumagalli, M Muschalik, P Kolpaczki, E Hüllermeier, B Hammer Advances in Neural Information Processing Systems 36, 2024 | 14 | 2024 |
| Incremental permutation feature importance (iPFI): towards online explanations on data streams F Fumagalli, M Muschalik, E Hüllermeier, B Hammer Machine Learning 112 (12), 4863-4903, 2023 | 12 | 2023 |
| Approximating the shapley value without marginal contributions P Kolpaczki, V Bengs, M Muschalik, E Hüllermeier arXiv preprint arXiv:2302.00736, 2023 | 12 | 2023 |
| Agnostic explanation of model change based on feature importance M Muschalik, F Fumagalli, B Hammer, E Hüllermeier KI-Künstliche Intelligenz 36 (3), 211-224, 2022 | 12 | 2022 |
| isage: An incremental version of SAGE for online explanation on data streams M Muschalik, F Fumagalli, B Hammer, E Hüllermeier Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 5 | 2023 |
| Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles M Muschalik, F Fumagalli, B Hammer, E Hüllermeier Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 14388 …, 2024 | 4 | 2024 |
| iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios M Muschalik, F Fumagalli, R Jagtani, B Hammer, E Hüllermeier World Conference on Explainable Artificial Intelligence, 177-194, 2023 | 2 | 2023 |
| KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions F Fumagalli, M Muschalik, P Kolpaczki, E Hüllermeier, B Hammer arXiv preprint arXiv:2405.10852, 2024 | | 2024 |
| SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification P Kolpaczki, M Muschalik, F Fumagalli, B Hammer, E Hüllermeier arXiv preprint arXiv:2401.13371, 2024 | | 2024 |
| On Feature Removal for Explainability in Dynamic Environments F Fumagalli, M Muschalik, E Hüllermeier, B Hammer ESANN 2023 proceedings, 2023 | | 2023 |
| Identifying Trends in Feature Attributions during Training of Neural Networks E Terzieva, M Muschalik, P Hofman, E Hüllermeier | | |
| On Explaining Model Change Based on Feature Importance M Muschalik, F Fumagalli, B Hammer, E Hüllermeier Book of Abstracts, 198, 0 | | |
Eyke HüllermeierProfessor of Computer Science, Paderborn University在 upb.de 的电子邮件经过验证
