Bardh Prenkaj
Orcid: 0000-0002-2991-2279
According to our database1,
Bardh Prenkaj
authored at least 29 papers
between 2017 and 2024.
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Bibliography
2024
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges.
ACM Comput. Surv., July, 2024
Unsupervised Detection of Behavioural Drifts With Dynamic Clustering and Trajectory Analysis.
IEEE Trans. Knowl. Data Eng., May, 2024
Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences.
CoRR, 2024
Proceedings of the Explainable Artificial Intelligence, 2024
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024
Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
A self-supervised algorithm to detect signs of social isolation in the elderly from daily activity sequences.
Artif. Intell. Medicine, January, 2023
CoRR, 2023
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection.
CoRR, 2023
Machine Learning for Visualization Recommendation Systems: Open Challenges and Future Directions.
CoRR, 2023
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
CoRR, 2022
Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence co-located with 21th International Conference of the Italian Association for Artificial Intelligence(AIxIA 2022), Udine, Italy, November 28, 2022
2021
Future Gener. Comput. Syst., 2021
A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses.
ACM Comput. Surv., 2021
C<sub>o</sub>R<sub>o</sub>NN<sub>a</sub>: a deep sequential framework to predict epidemic spread.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021
2020
A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020
Challenges and Solutions to the Student Dropout Prediction Problem in Online Courses.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020
2019
MIMOSE: multimodal interaction for music orchestration sheet editors - An integrable multimodal music editor interaction system.
Multim. Tools Appl., 2019
2018
2017
Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2017, 2017