@inproceedings{anonymous2025adaptive,title={Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection},author={Splieth\"{o}ver, Maximilian and Knebler, Tim and Fumagalli, Fabian and Muschalik, Maximilian and Hammer, Barbara Eva and H\"{u}llermeier, Eyke and Wachsmuth, Henning},booktitle={The 2025 Annual Conference of the Nations of the Americas Chapter of the ACL},year={2025},url={https://openreview.net/forum?id=epbOeozRRX},}
ICLR 2025
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik*, Fabian Fumagalli*, Paolo Frazzetto, Janine Strotherm, Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, and Barbara Hammer
In The Thirteenth International Conference on Learning Representations, 2025
@inproceedings{fumagalli2025exact,title={Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks},author={Muschalik, Maximilian and Fumagalli, Fabian and Frazzetto, Paolo and Strotherm, Janine and Hermes, Luca and Sperduti, Alessandro and H{\"u}llermeier, Eyke and Hammer, Barbara},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},url={https://openreview.net/forum?id=9tKC0YM8sX},}
AISTATS 2025
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory
Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, and Julia Herbinger
In The 28th International Conference on Artificial Intelligence and Statistics, 2025
@inproceedings{fumagalli2024unifyingfeaturebasedexplanationsfunctional,title={Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory},author={Fumagalli, Fabian and Muschalik, Maximilian and Hüllermeier, Eyke and Hammer, Barbara and Herbinger, Julia},booktitle={The 28th International Conference on Artificial Intelligence and Statistics},year={2025},}
2024
NeurIPS 2024
shapiq: Shapley Interactions for Machine Learning
Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, and Eyke Hüllermeier
In The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024
@inproceedings{muschalik2024shapiq,title={shapiq: Shapley Interactions for Machine Learning},author={Muschalik, Maximilian and Baniecki, Hubert and Fumagalli, Fabian and Kolpaczki, Patrick and Hammer, Barbara and H\"{u}llermeier, Eyke},booktitle={The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track},year={2024},url={https://openreview.net/forum?id=knxGmi6SJi},}
ICML 2024
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, and Barbara Hammer
In Forty-first International Conference on Machine Learning (ICML), 2024
@inproceedings{Fumagalli.2024,title={Kernel{SHAP}-{IQ}: Weighted Least Square Optimization for Shapley Interactions},author={Fumagalli, Fabian and Muschalik, Maximilian and Kolpaczki, Patrick and H{\"u}llermeier, Eyke and Hammer, Barbara},year={2024},booktitle={Forty-first International Conference on Machine Learning (ICML)},url={https://openreview.net/forum?id=d5jXW2H4gg},}
AAAI 2024
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
Maximilian Muschalik*, Fabian Fumagalli*, Barbara Hammer, and Eyke Hüllermeier
In Thirty-Eighth AAAI Conference on Artificial Intelligence, (AAAI), 2024
@inproceedings{Muschalik.2024,title={Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles},author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and H{\"{u}}llermeier, Eyke},year={2024},booktitle={Thirty-Eighth {AAAI} Conference on Artificial Intelligence, (AAAI)},publisher={{AAAI} Press},pages={14388--14396},doi={10.1609/AAAI.V38I12.29225},url={https://doi.org/10.1609/aaai.v38i12.29225},}
AISTATS 2024
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification
Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, and Eyke Hüllermeier
In International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
@inproceedings{Kolpaczki.2024,title={{SVARM-IQ:} Efficient Approximation of Any-order Shapley Interactions through Stratification},author={Kolpaczki, Patrick and Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and H{\"{u}}llermeier, Eyke},year={2024},booktitle={International Conference on Artificial Intelligence and Statistics (AISTATS)},publisher={{PMLR}},series={Proceedings of Machine Learning Research},volume={238},pages={3520--3528},url={https://proceedings.mlr.press/v238/kolpaczki24a.html},}
IJCNN 2024
No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
Philip Kenneweg, Tristan Kenneweg, Fabian Fumagalli, and Barbara Hammer
In International Joint Conference on Neural Networks, (IJCNN), 2024
@inproceedings{DBLP:conf/ijcnn/KennewegKFH24,author={Kenneweg, Philip and Kenneweg, Tristan and Fumagalli, Fabian and Hammer, Barbara},title={No learning rates needed: Introducing {SALSA} - Stable Armijo Line
Search Adaptation},year={2024},booktitle={International Joint Conference on Neural Networks, {(IJCNN)}},pages={1--8},publisher={{IEEE}},url={https://doi.org/10.1109/IJCNN60899.2024.10650124},doi={10.1109/IJCNN60899.2024.10650124},}
2023
NeurIPS 2023
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
Fabian Fumagalli*, Maximilian Muschalik*, Patrick Kolpaczki, Eyke Hüllermeier, and Barbara Hammer
In Advances in Neural Information Processing Systems 36 (NeurIPS), 2023
@inproceedings{Fumagalli.2023b,title={{SHAP-IQ:} Unified Approximation of any-order Shapley Interactions},author={Fumagalli, Fabian and Muschalik, Maximilian and Kolpaczki, Patrick and H{\"{u}}llermeier, Eyke and Hammer, Barbara},year={2023},booktitle={Advances in Neural Information Processing Systems 36 (NeurIPS)},url={https://openreview.net/forum?id=IEMLNF4gK4},}
MLJ
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams
Fabian Fumagalli*, Maximilian Muschalik*, Eyke Hüllermeier, and Barbara Hammer
@article{Fumagalli.2023a,title={Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams},author={Fumagalli, Fabian and Muschalik, Maximilian and H{\"{u}}llermeier, Eyke and Hammer, Barbara},year={2023},journal={Machine Learning},volume={112},number={12},pages={4863--4903},doi={10.1007/S10994-023-06385-Y},url={https://doi.org/10.1007/s10994-023-06385-y},}
xAI 2023
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios
Maximilian Muschalik*, Fabian Fumagalli*, Rohit Jagtani, Barbara Hammer, and Eyke Hüllermeier
In World Conference of Explainable Artificial Intelligence (xAI), 2023
@inproceedings{Muschalik.2023,title={iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios},author={Muschalik, Maximilian and Fumagalli, Fabian and Jagtani, Rohit and Hammer, Barbara and H{\"{u}}llermeier, Eyke},year={2023},booktitle={World Conference of Explainable Artificial Intelligence (xAI)},publisher={Springer},series={Communications in Computer and Information Science},volume={1901},pages={177--194},doi={10.1007/978-3-031-44064-9\_11},url={https://doi.org/10.1007/978-3-031-44064-9\_11},}
ECML PKDD 2023
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
Maximilian Muschalik*, Fabian Fumagalli*, Barbara Hammer, and Eyke Hüllermeier
In Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, (ECML PKDD), 2023
@inproceedings{Muschalik.2023a,title={iSAGE: An Incremental Version of {SAGE} for Online Explanation on Data Streams},author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and H{\"{u}}llermeier, Eyke},booktitle={Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ({ECML} {PKDD})},publisher={Springer},series={Lecture Notes in Computer Science},volume={14171},year={2023},pages={428--445},doi={10.1007/978-3-031-43418-1\_26},url={https://doi.org/10.1007/978-3-031-43418-1\_26},}
ESANN 2023
On Feature Removal for Explainability in Dynamic Environments
Fabian Fumagalli*, Maximilian Muschalik*, Eyke Hüllermeier, and Barbara Hammer
In 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2023
@inproceedings{Fumagalli.2023,title={On Feature Removal for Explainability in Dynamic Environments},author={Fumagalli, Fabian and Muschalik, Maximilian and H{\"{u}}llermeier, Eyke and Hammer, Barbara},year={2023},booktitle={31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning ({ESANN})},doi={10.14428/ESANN/2023.ES2023-148},url={https://doi.org/10.14428/esann/2023.ES2023-148},}
2022
KI Journal
Agnostic Explanation of Model Change based on Feature Importance
Maximilian Muschalik*, Fabian Fumagalli*, Barbara Hammer, and Eyke Hüllermeier
@article{Muschalik.2022,title={Agnostic Explanation of Model Change based on Feature Importance},author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and H{\"{u}}llermeier, Eyke},year={2022},journal={K{\"{u}}nstliche Intelligenz},volume={36},number={3},pages={211--224},doi={10.1007/s13218-022-00766-6},}