no code implementations • 23 Jan 2024 • Philip Mavrepis, Georgios Makridis, Georgios Fatouros, Vasileios Koukos, Maria Margarita Separdani, Dimosthenis Kyriazis
The field of Explainable Artificial Intelligence (XAI) often focuses on users with a strong technical background, making it challenging for non-experts to understand XAI methods.
no code implementations • 1 Dec 2023 • Georgios Makridis, Vasileios Koukos, Georgios Fatouros, Dimosthenis Kyriazis
In the domain of Mobility Data Science, the intricate task of interpreting models trained on trajectory data, and elucidating the spatio-temporal movement of entities, has persistently posed significant challenges.
no code implementations • 28 Nov 2023 • Georgios Makridis, Georgios Fatouros, Vasileios Koukos, Dimitrios Kotios, Dimosthenis Kyriazis, Ioannis Soldatos
Although much work has been done on explainability in the computer vision and natural language processing (NLP) fields, there is still much work to be done to explain methods applied to time series as time series by nature can not be understood at first sight.