| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 4 | Ephrem Tibebe Mekonnen; Longo L., Dondio P. | LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations | IEEE Access | 2025 | @ARTICLE{MekonnenLongo2025, author={Mekonnen, Ephrem Tibebe and Longo, Luca and Dondio, Pierpaolo}, journal={IEEE Access}, title={LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations}, year={2025}, volume={}, number={}, pages={1-1}, keywords={Time series analysis;Adaptation models;Explainable AI;Predictive models;Data models;Closed box;Perturbation methods;Computational modeling;Deep learning;Kernel;Explainable Artificial Intelligence;Model-agnostic;Time series;Post hoc;Deep learning;XAI}, doi={10.1109/ACCESS.2025.3625442}} [Close]
| Time series analysis • Adaptation models • Explainable AI • Predictive models • Data models • Closed box • Perturbation methods • Computational modeling • Deep learning • Kernel • Explainable Artificial Intelligence • Model-agnostic • Time series • Post hoc • Deep learning • XAI |
| 3 | Mekonnen E. T., Longo L., Dondio P. | Interpreting Black-Box Time Series Classifiers using Parameterised Event Primitives | Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024) | 2024 |
@inproceedings{Mekonnen2024, title={Interpreting Black-Box Time Series Classifiers using Parameterised Event Primitives}, author={Mekonnen, Ephrem. T., Longo, Luca, and Dondio, Pierpaolo}, year={2024}, booktitle = {Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024), Valletta, Malta, 17-19 July, 2024}, publisher = {CEUR-WS.org}, url = {https://ceur-ws.org/Vol-3793/paper_9.pdf}, volume = {3793}, series = {{CEUR} Workshop Proceedings}, editor = {Luca Longo, Weiru Liu, Grégoire Montavon} pages={65-72} } [Close]
| Explainable Artificial Intelligence • Model-Agnostic • Time Series • Post-hoc • Deep Learning • Machine Learning • Event primitives • Time-series |
| 2 | Mekonnen E.T., Longo L., Dondio P. | A global model-agnostic rule-based XAI method based on Parameterized Event Primitives for time series classifiers | Frontiers Artificial Intelligence | 2024 |
@ARTICLE{10.3389/frai.2024.1381921, AUTHOR={Mekonnen, Ephrem T. and Dondio, Pierpaolo and Longo, Luca }, TITLE={A Global Model-Agnostic Rule-Based XAI Method based on Parameterised Event Primitives for Time Series Classifiers}, JOURNAL={Frontiers in Artificial Intelligence}, VOLUME={7}, YEAR={2024}, URL={https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2024.1381921}, DOI={10.3389/frai.2024.1381921}, ISSN={2624-8212}, } [Close]
| Deep learning • Explainable Artificial Intelligence • time series classification • decision tree •
model agnostic • post-hoc • Machine Learning |
| 1 | Mekonnen E.T., Dondio P., Longo L. | Explaining Deep Learning Time Series Classification Models using a Decision Tree-Based Post-Hoc XAI Method | Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) | 2023 |
@INPROCEEDINGS{Mekonnen2023, author={Mekonnen, E.T., Dondio P., and Longo L.}, booktitle={Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023)}, title={Explaining Deep Learning Time Series Classification Models using a Decision Tree-Based Post-Hoc XAI Method}, year={2023}, volume={3554}, number={}, pages={71-76}, publisher={CEUR} } [Close]
| Explainable Artificial Intelligence • Deep Learning • Time Series • Classification • Decision-Trees • Machine Learning • Post-hoc |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |