publications

2026

1. AAAI 2026 (Oral)

   HyperSHAP: Shapley Values and Interactions for Hyperparameter Importance

   Marcel Wever, Maximilian Muschalik, Fabian Fumagalli, and Marius Lindauer

   In Fortieth AAAI Conference on Artificial Intelligence, (AAAI), 2026

2025

1. NeurIPS 2025

   Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions

   Hubert Baniecki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, and Przemyslaw Biecek

   In Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 2025
2. EMNLP 2025

   Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions

   Meghdut Sengupta, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Debanjan Ghosh, and Henning Wachsmuth

   In Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
3. NAACL 2025 (Oral)

   Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection

   Maximilian Spliethöver, Tim Knebler, Fabian Fumagalli, Maximilian Muschalik, Barbara Eva Hammer, Eyke Hüllermeier, and Henning Wachsmuth

   In The 2025 Annual Conference of the Nations of the Americas Chapter of the ACL, 2025

   Bib

   @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://aclanthology.org/2025.naacl-long.122/},
   }

4. 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

   Bib

   @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},
   }

5. 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

   Bib Website

   @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

1. 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

   Bib Poster Website

   @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},
   }

2. 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

   Bib Poster

   @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},
   }

3. 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

   DOI Bib Poster

   @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},
   }

4. 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

   Bib

   @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},
   }

5. 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

   DOI Bib

   @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

1. 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

   Bib Poster

   @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},
   }

2. MLJ

   Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams

   Fabian Fumagalli^*, Maximilian Muschalik^*, Eyke Hüllermeier, and Barbara Hammer

   Machine Learning, 2023

   DOI Bib Poster Slides

   @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},
   }

3. 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

   DOI Bib Slides

   @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},
   }

4. 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

   DOI Bib Poster Slides

   @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},
   }

5. 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

   DOI Bib Poster

   @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

1. KI Journal

   Agnostic Explanation of Model Change based on Feature Importance

   Maximilian Muschalik^*, Fabian Fumagalli^*, Barbara Hammer, and Eyke Hüllermeier

   Künstliche Intelligenz, 2022

   DOI Bib Website

   @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},
   }