A Smart Peephole on the Cloud. - Maria De Marsico; Eugenio Nemmi; Bardh Prenkaj; Gabriele Saturni (ICIAP Workshops, 2017)

House in the (Biometric) Cloud: A Possible Application. - Maria De Marsico; Eugenio Nemmi; Bardh Prenkaj; Gabriele Saturni (IEEE Cloud Comput., 2018)

MIMOSE: multimodal interaction for music orchestration sheet editors - An integrable multimodal music editor interaction system. - Andrea Coletta; Maria De Marsico; Emanuele Panizzi; Bardh Prenkaj; Domenicomichele Silvestri (Multim. Tools Appl., 2019)

Challenges and Solutions to the Student Dropout Prediction Problem in Online Courses. - Bardh Prenkaj; Giovanni Stilo; Lorenzo Madeddu (CIKM, 2020)

A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction. - Bardh Prenkaj; Paola Velardi; Damiano Distante; Stefano Faralli 001 (CIKM, 2020)

Unsupervised Boosting-Based Autoencoder Ensembles for Outlier Detection. - Hamed Sarvari; Carlotta Domeniconi; Bardh Prenkaj; Giovanni Stilo (PAKDD (1), 2021)

CoRoNNa: a deep sequential framework to predict epidemic spread. - Dario Aragona; Luca Podo; Bardh Prenkaj; Paola Velardi (SAC, 2021)

A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses. - Bardh Prenkaj; Paola Velardi; Giovanni Stilo; Damiano Distante; Stefano Faralli 001 (ACM Comput. Surv., 2021)

Hidden space deep sequential risk prediction on student trajectories. - Bardh Prenkaj; Damiano Distante; Stefano Faralli 001; Paola Velardi (Future Gener. Comput. Syst., 2021)

Ensemble Approaches for Graph Counterfactual Explanations. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo; Alessandro Celi; Ernesto Luis Estevanell-Valladares; Daniel Alejandro Valdés Pérez (XAI.it@AI*IA, 2022)

A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo; Fosca Giannotti (CoRR, 2022)

Latent deep sequential learning of behavioural sequences. - Bardh Prenkaj (2022)

Are we certain it's anomalous? - Alessandro Flaborea; Bardh Prenkaj; Bharti Munjal; Marco Aurelio Sterpa; Dario Aragona; Luca Podo; Fabio Galasso (CVPR Workshops, 2023)

Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection. - Alessandro Flaborea; Luca Collorone; Guido Maria D'Amely di Melendugno; Stefano D'Arrigo; Bardh Prenkaj; Fabio Galasso (ICCV, 2023)

Revisiting CounteRGAN for Counterfactual Explainability of Graphs. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo (Tiny Papers @ ICLR, 2023)

Are Generative-Based Graph Counterfactual Explainers Worth It? - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo (PKDD/ECML Workshops (3), 2023)

Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes. - Bardh Prenkaj; Mario Villaizán-Vallelado; Tobias Leemann; Gjergji Kasneci (PKDD/ECML Workshops (1), 2023)

Developing and Evaluating Graph Counterfactual Explanation with GRETEL. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo (WSDM, 2023)

Machine Learning for Visualization Recommendation Systems: Open Challenges and Future Directions. - Luca Podo; Bardh Prenkaj; Paola Velardi (CoRR, 2023)

Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection. - Alessandro Flaborea; Luca Collorone; Guido D'Amely; Stefano D'Arrigo; Bardh Prenkaj; Fabio Galasso (CoRR, 2023)

A self-supervised algorithm to detect signs of social isolation in the elderly from daily activity sequences. - Bardh Prenkaj; Dario Aragona; Alessandro Flaborea; Fabio Galasso; Saverio Gravina; Luca Podo; Emilia Reda; Paola Velardi (Artif. Intell. Medicine, 2023)

Robust Stochastic Graph Generator for Counterfactual Explanations. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo (AAAI, 2024)

Semantically Guided Representation Learning For Action Anticipation. - Anxhelo Diko; Danilo Avola; Bardh Prenkaj; Federico Fontana; Luigi Cinque (ECCV (28), 2024)

Workshop on Discovering Drift Phenomena in Evolving Data Landscape (DELTA). - Marco Piangerelli; Bardh Prenkaj; Ylenia Rotalinti; Ananya Joshi 001; Giovanni Stilo (KDD, 2024)

Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals. - Bardh Prenkaj; Mario Villaizán-Vallelado; Tobias Leemann; Gjergji Kasneci (KDD, 2024)

GRETEL 2.0: Generation and Evaluation of Graph Counterfactual Explanations Evolved. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo (ECML/PKDD (8), 2024)

Towards Non-adversarial Algorithmic Recourse. - Tobias Leemann; Martin Pawelczyk; Bardh Prenkaj; Gjergji Kasneci (xAI (3), 2024)

Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences. - Davide Gabrielli; Bardh Prenkaj; Paola Velardi (CoRR, 2024)

Unsupervised Detection of Behavioural Drifts With Dynamic Clustering and Trajectory Analysis. - Bardh Prenkaj; Paola Velardi (IEEE Trans. Knowl. Data Eng., 2024)

A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges. - Mario Alfonso Prado-Romero; Bardh Prenkaj; Giovanni Stilo; Fosca Giannotti (ACM Comput. Surv., 2024)

RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting. - Shuo Yang; Bardh Prenkaj; Gjergji Kasneci (AAAI, 2025)

Probabilistic Aggregation and Targeted Embedding Optimization for Collective Moral Reasoning in Large Language Models. - Chenchen Yuan; Zheyu Zhang 007; Shuo Yang; Bardh Prenkaj; Gjergji Kasneci (ACL (Findings), 2025)

TRADES: Generating Realistic Market Simulations with Diffusion Models. - Leonardo Berti; Bardh Prenkaj; Paola Velardi (CoRR, 2025)

Agnostic Visual Recommendation Systems: Open Challenges and Future Directions. - Luca Podo; Bardh Prenkaj; Paola Velardi (IEEE Trans. Vis. Comput. Graph., 2025)

Graph Style Transfer for Counterfactual Explainability. - Bardh Prenkaj; Efstratios Zaradoukas; Gjergji Kasneci (CoRR, 2025)

SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification. - Shuo Yang; Bardh Prenkaj; Gjergji Kasneci (CoRR, 2025)

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models. - Zheyu Zhang 007; Shuo Yang; Bardh Prenkaj; Gjergji Kasneci (CoRR, 2025)

Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs. - Shuo Yang; Zheyu Zhang 007; Bardh Prenkaj; Gjergji Kasneci (CoRR, 2025)

AI on the Pulse: Real-Time Health Anomaly Detection with Wearable and Ambient Intelligence. - Davide Gabrielli; Bardh Prenkaj; Paola Velardi; Stefano Faralli 001 (CoRR, 2025)