Mado Ntekouli (M.)

Ntekouli, M., Bombassei De Bona, F., Gjoreski, M., & Spanakis, G. (2025). Evaluating the Quality of Counterfactual Explanations in Multivariate Time-Series. In M. Beigl, G. Jacucci, S. Sigg, Y. Xiao, J. E. Bardram, E. E. Tsiropoulou, & C. Xu (Eds.), UbiComp Companion 2025 - Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1674-1678). Association for Computing Machinery, Inc. https://doi.org/10.1145/3714394.3756321

Vered, M., Hassan, T., Ntekouli, M., Bae, S. W., & Gjoreski, M. (2025). XAI for U 2025: 2$nd$ International Workshop on Explainable AI for Ubiquitous, Pervasive and Wearable Computing. In M. Beigl, G. Jacucci, S. Sigg, Y. Xiao, J. E. Bardram, E. E. Tsiropoulou, & C. Xu (Eds.), UbiComp Companion 2025 - Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1670-1673). Association for Computing Machinery, Inc. https://doi.org/10.1145/3714394.3750557

Ntekouli, M., Spanakis, G., Waldorp, L., & Roefs, A. (2024). Explaining Clustering of Ecological Momentary Assessment Data Through Temporal and Feature Attention. In L. Longo, S. Lapuschkin, & C. Seifert (Eds.), Explaining Clustering of Ecological Momentary Assessment Data Through Temporal and Feature Attention (pp. 75-99). Article Chapter 5 Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-63797-1_5

Ntekouli, M., Spanakis, G., Waldorp, L., & Roefs, A. (2024). Exploiting Individual Graph Structures to Enhance Ecological Momentary Assessment (EMA) Forecasting. In 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW) (pp. 158-166). The IEEE. https://doi.org/10.1109/ICDEW61823.2024.00027

Ntekouli, M., Spanakis, G., Waldorp, L., & Roefs, A. (2023). Clustering Individuals Based on Multivariate EMA Time-Series Data. In M. Wiberg, D. Molenaar, J. González, J.-S. Kim, & H. Hwang (Eds.), Quantitative Psychology (pp. 161-171). Springer, Cham. https://doi.org/10.1007/978-3-031-27781-8_15

Ntekouli, M., Spanakis, G., Roefs, A., & Waldorp, L. (2022). Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data. In T. Bouadi, E. Fromont, & E. Hüllermeier (Eds.), Advances in Intelligent Data Analysis XX - 20th International Symposium on Intelligent Data Analysis, IDA 2022, Proceedings (pp. 199–211). Springer, Cham. https://doi.org/10.1007/978-3-031-01333-1_16