| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 4 | Ahmed T., Biecek P. Longo L. | Latent Space Interpretation and Mechanistic Clipping of Subject-Specific Variational Autoencoders of EEG Topographic Maps for Artefacts Reduction | eXplainable Artificial Intelligence, The World Conference (xAI-2025) | 2025 |   
@InProceedings{AhmedLongo2025, author="Ahmed, Taufique and Biecek, Przemyslaw and Longo, Luca", editor="Guidotti, Riccardo and Schmid, Ute and Longo, Luca", title="Latent Space Interpretation and Mechanistic Clipping of Subject-Specific Variational Autoencoders of EEG Topographic Maps for Artefacts Reduction", booktitle="Explainable Artificial Intelligence", year="2026", publisher="Springer Nature Switzerland", address="Cham", pages="327--350", isbn="978-3-032-08327-2" } [Close]
| Electroencephalography •
Spectral topographic maps •
Subject-specific •
Variational autoencoder •
Latent space •
interpretability •
Artefacts removal •
Deep learning •
full automation •
explainable AI |
| 3 | Ceschin M., Arrighi L., Longo L., Barbon Junior S. | Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest | eXplainable Artificial Intelligence, The World Conference (xAI-2025) | 2025 |
@InProceedings{CeschinLongo2025, author="Ceschin, Matteo and Arrighi, Leonardo and Longo, Luca and Barbon Junior, Sylvio", editor="Guidotti, Riccardo and Schmid, Ute and Longo, Luca", title="Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest", booktitle="Explainable Artificial Intelligence", year="2026", publisher="Springer Nature Switzerland", address="Cham", pages="271--293", isbn="978-3-032-08324-1" } [Close]
| Ensemble Learning • Outliers • Explainable Artificial Intelligence • Interpretability • Anomalies • Tree-based Ensemble Model |
| 2 | Kopanja M., Savic M., Longo L | Enhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation | Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025) | 2025 |
@inproceedings{, title={Enhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation}, author={Kopanja, Marija and Savi?, Miloš and Longo, Luca}, year={2025}, booktitle = {Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025), Istanbul, Turkey, 9-11 July, 2025}, publisher = {CEUR-WS.org}, volume = {4017}, series = {{CEUR} Workshop Proceedings}, editor = {Przemys?aw Biecek, Slawomir Nowaczyk, Gitta Kutyniok, Luca Longo}, pages={129-136}, url={https://ceur-ws.org/Vol-4017/paper_17.pdf} } [Close]
| Explainable artificial intelligence • Cost-sensitive decision tree • Surrogate modeling • Rule extraction • Tree-based
methods • Model-agnostic explanations • Rule-based systems • Interpretability • Machine Learning. |
| 1 | Gupta G., Qureshi M.A., Longo L. | A Global Post Hoc XAI Method For Interpreting LSTM Using Deterministic Finite State Automata | The Irish conference on Artificial Intelligence and Cognitive Science | 2025 | 
@inproceedings{GuptaLongo2024, title={A Global Post Hoc XAI Method For Interpreting LSTM Using Deterministic Finite State Automata}, author={Gupta G., Qureshi M.A., Longo, L.}, year={2024}, booktitle = { Proceedings of The 32nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2024)}, publisher = {CEUR-WS.org}, volume = {3910}, series = {{CEUR} Workshop Proceedings}, pages={26-38} } [Close]
| RNN • interpretability • Explainable AI • LSTM • Deterministic Finite State Automata • k-means clustering • Recurrent Neural Networks |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |