Fabian Fumagalli

According to our database, Fabian Fumagalli authored at least 28 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Proxy-Based Approximation of Shapley and Banzhaf Interactions.

Santo M. A. R. Thies, Hubert Baniecki, R. Teal Witter, Eyke Hüllermeier, Maximilian Muschalik, Fabian Fumagalli

CoRR, May, 2026

Attributions All the Way Down? The Metagame of Interpretability.

Hubert Baniecki, Przemyslaw Biecek, Fabian Fumagalli

CoRR, May, 2026

Functional Decomposition and Shapley Interactions for Interpreting Survival Models.

Sophie Hanna Langbein, Hubert Baniecki, Fabian Fumagalli, Niklas Koenen, Marvin N. Wright, Julia Herbinger

CoRR, February, 2026

Exactly Computing do-Shapley Values.

R. Teal Witter, Álvaro Parafita, Tomas Garriga, Maximilian Muschalik, Fabian Fumagalli, Axel Brando, Lucas Rosenblatt

CoRR, February, 2026

An Odd Estimator for Shapley Values.

Fabian Fumagalli, Landon Butler, Justin Singh Kang, Kannan Ramchandran, R. Teal Witter

CoRR, February, 2026

GRANITE: A Generalized Regional Framework for Identifying Agreement in Feature-Based Explanations.

Julia Herbinger, Gabriel Laberge, Maximilian Muschalik, Yann Pequignot, Marvin N. Wright, Fabian Fumagalli

CoRR, January, 2026

PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression.

Fabian Fumagalli, R. Teal Witter, Christopher Musco

CoRR, January, 2026

HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization.

Marcel Wever, Maximilian Muschalik, Fabian Fumagalli, Marius Lindauer

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions.

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

CoRR, August, 2025

HyperSHAP: Shapley Values and Interactions for Hyperparameter Importance.

Marcel Wever, Maximilian Muschalik, Fabian Fumagalli, Marius Lindauer

CoRR, February, 2025

Explainable AI: A Unified Approach Based on Cooperative Game Theory.

Fabian Fumagalli

PhD thesis, 2025

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

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

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 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, Barbara Hammer

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Explaining Outliers using Isolation Forest and Shapley Interactions.

Roel Visser, Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer

Proceedings of the 33rd European Symposium on Artificial Neural Networks, 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, Henning Wachsmuth

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory.

Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Explaining Change in Models and Data with Global Feature Importance and Effects.

Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), 2024

shapiq: Shapley Interactions for Machine Learning.

Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, Eyke Hüllermeier

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation.

Philip Kenneweg, Tristan Kenneweg, Fabian Fumagalli, Barbara Hammer

Proceedings of the International Joint Conference on Neural Networks, 2024

KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.

Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification.

Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

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

Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

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

Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer

Mach. Learn., December, 2023

iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios.

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

Proceedings of the Explainable Artificial Intelligence, 2023

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

Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

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

Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Feature Removal for Explainability in Dynamic Environments.

Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022

Agnostic Explanation of Model Change based on Feature Importance.

Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

Künstliche Intell., 2022