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TempXAI@PKDD/ECML 2024: Vilnius, Lithuania
- Zahraa S. Abdallah, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Matthias Jakobs, Emmanuel Müller, Maximilian Muschalik, Panagiotis Papapetrou, Amal Saadallah, George Tzagkarakis:
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), Vilnius, Lithuania, September 9th, 2024. CEUR Workshop Proceedings 3761, CEUR-WS.org 2024
Extended Abstracts
- Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
Explaining Change in Models and Data with Global Feature Importance and Effects. 1-6 - Amal Saadallah, Matthias Jakobs:
Online Explainable Forecasting using Regions of Competence. 7-11
Research Papers
- Udo Schlegel, Daniel A. Keim, Tobias Sutter:
Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series. 12-27 - Jan Arne Telle, Cèsar Ferri, Brigt Arve Toppe Håvardstun:
Optimal Robust Simplifications for Explaining Time Series Classifications. 28-43 - Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder:
Interpreting Outliers in Time Series Data through Decoding Autoencoder. 44-57 - Parisa Jamshidi, Slawomir Nowaczyk, Mahmoud Rahat, Zahra Taghiyarrenani:
Explainable Federated Learning by Incremental Decision Trees. 58-69
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