Publications

2024

1. ICML

   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), 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 2024)},
     url = {https://openreview.net/forum?id=d5jXW2H4gg},
   }

2. AISTATS

   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), 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 2024)},
     publisher = {{PMLR}},
     series = {Proceedings of Machine Learning Research},
     volume = {238},
     pages = {3520--3528},
   }

3. AAAI

   Approximating the Shapley Value without Marginal Contributions

   Patrick Kolpaczki, Viktor Bengs, Maximilian Muschalik, and Eyke Hüllermeier

   In Thirty-Eighth AAAI Conference on Artificial Intelligence, (AAAI 2024), 2024

   Bib

   @inproceedings{Kolpaczki.2024a,
     title = {Approximating the Shapley Value without Marginal Contributions},
     author = {Kolpaczki, Patrick and Bengs, Viktor and Muschalik, Maximilian and H{\"{u}}llermeier, Eyke},
     year = {2024},
     booktitle = {Thirty-Eighth {AAAI} Conference on Artificial Intelligence, (AAAI 2024)},
     publisher = {{AAAI} Press},
     pages = {13246--13255},
     doi = {10.1609/AAAI.V38I12.29225},
     url = {https://doi.org/10.1609/aaai.v38i12.29225},
   }

4. AAAI

   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), 2024

   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 2024)},
     publisher = {{AAAI} Press},
     pages = {14388--14396},
     doi = {10.1609/AAAI.V38I12.29225},
     url = {https://doi.org/10.1609/aaai.v38i12.29225},
   }

5. Front. AI

   Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments

   Stefan Haas, Konstantin Hegestweiler, Michael Rapp, Maximilian Muschalik, and Eyke Hüllermeier

   Front. Artif. Intell., 2024

   Bib

   @article{Haas.2024,
     title = {Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments},
     author = {Haas, Stefan and Hegestweiler, Konstantin and Rapp, Michael and Muschalik, Maximilian and H{\"{u}}llermeier, Eyke},
     year = {2024},
     journal = {Front. Artif. Intell.},
     volume = {7},
     number = {12},
     pages = {1471208},
     doi = {https://doi.org/10.3389/frai.2024.1471208},
   }

6. NeurIPS

   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 Datasets and Benchmarks Track (NeurIPS 2024), 2024

   Bib Poster Website

   @inproceedings{Muschalik.2024a,
     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},
     year = {2024},
     booktitle = {The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS 2024)},
     url = {https://openreview.net/forum?id=knxGmi6SJi},
   }

2023

1. ESANN

   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), 2023

   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} 2023)},
     doi = {10.14428/ESANN/2023.ES2023-148},
     url = {https://doi.org/10.14428/esann/2023.ES2023-148},
   }

2. MLJ

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

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

   Mach. Learn., 2023

   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 = {Mach. Learn.},
     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. NeurIPS

   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), 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 2023)},
     url = {https://openreview.net/forum?id=IEMLNF4gK4},
   }

4. xAI

   iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios

   Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, and Eyke Hüllermeier

   2023

   Bib Slides

   @article{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 = {Explainable Artificial Intelligence - First World Conference (xAI 2023)},
     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},
   }

5. ECMLPKDD

   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), 2023

   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},
     year = {2023},
     booktitle = {Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ({ECML} {PKDD} 2023)},
     publisher = {Springer},
     series = {Lecture Notes in Computer Science},
     volume = {14171},
     pages = {428--445},
     doi = {10.1007/978-3-031-43418-1\_26},
     url = {https://doi.org/10.1007/978-3-031-43418-1\_26},
   }

2022

1. Künstliche Intell.

   Agnostic Explanation of Model Change based on Feature Importance

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

   Künstliche Intell., 2022

   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 Intell.},
     volume = {36},
     number = {3},
     pages = {211--224},
     doi = {10.1007/s13218-022-00766-6},
   }