Original: https://ceur-ws.org/Vol-3761/ | Mirror: https://ceur-ws.wikidata.dbis.rwth-aachen.de/Vol-3761/ | Year: 2024

Vol-3761
urn:nbn:de:0074-3761-3

Copyright © 2024 for the individual papers by the papers' authors. Copyright © 2024 for the volume as a collection by its editors. This volume and its papers are published under https://creativecommons.org/licenses/by/4.0/.

TempXAI 2024

Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024)
co-located with ECML-PKDD 2024

Vilnius, Lithuania, September 9th, 2024.

Edited by

Zahraa Abdallah
Fabian Fumagalli
Barbara Hammer
Eyke Hüllermeier
Matthias Jakobs
Emmanuel

Table of Contents

PDF
Explaining Change in Models and Data with Global Feature Importance and Effects 1-6 PDF
Eyke Hüllermeier, Fabian Fumagalli, Maximilian Muschalik, Barbara Hammer
Online Explainable Forecasting using Regions of Competence 7-11 PDF
Matthias Jakobs, Amal Saadallah
Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series 12-27 PDF
Tobias Sutter, Udo Schlegel, Daniel A. Keim
Optimal Robust Simplifications for Explaining Time Series Classifications 28-43 PDF
Brigt Arve Toppe Håvardstun, Jan Arne Telle, Cèsar Ferri
Interpreting Outliers in Time Series Data through Decoding Autoencoder 44-57 PDF
Christian Bartelt, Sascha Marton, Patrick Knab, Robert Fuder
Explainable Federated Learning by Incremental Decision Trees 58-69 PDF
Zahra Taghiyarrenani, Slawomir Nowaczyk, Parisa Jamshidi, Mahmoud Rahat

2024-09-17: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|