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• [7]
  

  2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2988165

  Muschalik, Maximilian, Fumagalli, Fabian, Hammer, Barbara, and Hüllermeier, Eyke. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles”. Proceedings of the AAAI Conference on Artificial Intelligence 38.13 (2024): 14388-14396.

  PUB | DOI
   
• [6]
  

  2023 | Konferenzbeitrag | PUB-ID: 2987580

  Fumagalli, Fabian, Muschalik, Maximilian, Kolpaczki, Patrick, Hüllermeier, Eyke, and Hammer, Barbara. “SHAP-IQ: Unified Approximation of any-order Shapley Interactions”. Advances in Neural Information Processing Systems 36 (NeurIPS 2023). 2023.

  PUB | Download (ext.) | arXiv
   
• [5]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2983756

  Fumagalli, Fabian, Muschalik, Maximilian, Hüllermeier, Eyke, and Hammer, Barbara. “On Feature Removal for Explainability in Dynamic Environments”. ESANN 2023 proceedings. 2023. 83-88.

  PUB | DOI
   
• [4]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983943

  Muschalik, Maximilian, Fumagalli, Fabian, Hammer, Barbara, and Hüllermeier, Eyke. “iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams”. Machine Learning and Knowledge Discovery in Databases: Research Track. European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part III. Ed. Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, and Francesco Bonchi. Cham: Springer Nature Switzerland, 2023. Lecture Notes in Computer Science. 428-445.

  PUB | DOI
   
• [3]
  

  2023 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2983727

  Fumagalli, Fabian, Muschalik, Maximilian, Hüllermeier, Eyke, and Hammer, Barbara. “Incremental permutation feature importance (iPFI): towards online explanations on data streams”. Machine Learning (2023).

  PUB | DOI | WoS
   
• [2]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983942

  Muschalik, Maximilian, Fumagalli, Fabian, Jagtani, Rohit, Hammer, Barbara, and Hüllermeier, Eyke. “iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios”. Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part I. Ed. Luca Longo. Cham: Springer Nature Switzerland, 2023. Communications in Computer and Information Science. 177-194.

  PUB | DOI
   
• [1]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2964421

  Muschalik, Maximilian, Fumagalli, Fabian, Hammer, Barbara, and Hüllermeier, Eyke. “Agnostic Explanation of Model Change based on Feature Importance”. KI - Künstliche Intelligenz (2022).

  PUB | DOI | Download (ext.) | WoS