VIZZARI GIUSEPPE

Bufano, F., Bordiu, C., Cecconello, T., Munari, M., Hopkins, A., Ingallinera, A., et al. (2024). Sifting the debris: Patterns in the SNR population with unsupervised ML methods. ASTRONOMY & ASTROPHYSICS, 690(October 2024), 1-17 [10.1051/0004-6361/202451096]. Detail

Masiero, E., Bursic, S., Trianni, V., Vizzari, G., Ognibene, D. (2024). In Search of Compositional Multi-Task Deep Architectures for Information Theoretic Field Exploration. In 20th IEEE International Conference on Automation Science and Engineering, CASE 2024 (pp.612-617). IEEE Computer Society [10.1109/CASE59546.2024.10711675]. Detail

Piskovskyi, V., Chimisso, R., Patania, S., Foulsham, T., Vizzari, G., Ognibene, D. (2024). Generalizability analysis of deep learning predictions of human brain responses to augmented and semantically novel visual stimuli. Intervento presentato a: Human-inspired Computer Vision - ECCV 2024 Workshop - 29th September 2024, Milan, Italy [10.48550/arXiv.2410.04497]. Detail

Spahiu, B., Briola, D., Sartori, R., Vizzari, G. (2024). A Data-Driven Approach Supporting Location Decisions for Docking Stations in Bike-Sharing Systems. In 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) (pp.4618-4625) [10.3233/faia241056]. Detail

Delfini, L., Spahiu, B., Vizzari, G. (2024). Visual Analytics for Sustainable Mobility: Usability Evaluation and Knowledge Acquisition for Mobility-as-a-Service (MaaS) Data Exploration. DIGITAL, 4(4), 821-845 [10.3390/digital4040041]. Detail