Alessandro BICCIATO
- Qualifica
- Assegnista
- Sito web
-
www.unive.it/persone/alessandro.bicciato (scheda personale)
- Struttura
-
Dipartimento di Scienze Ambientali, Informatica e Statistica
Sito web struttura: https://www.unive.it/dais
Minello G.; Bicciato A.; Rossi L.; Torsello A.; Cosmo L. GENERATING GRAPHS VIA SPECTRAL DIFFUSION , 13th International Conference on Learning Representations, ICLR 2025, International Conference on Learning Representations, ICLR, pp. 18077-18096, Convegno: 13th International Conference on Learning Representations, ICLR 2025, 2025
2025,
Articolo in Atti di convegno - Scheda ARCA: 10278/5100927
Minello, Giorgia; Zhang, Lingfeng; Bicciato, Alessandro; Rossi, Luca; Torsello, Andrea; Cosmo, Luca LESI-GNN: An Interpretable Graph Neural Network Based on Local Structures Embedding , Lecture Notes in Computer Science, Springer, pp. 72-81, Convegno: Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) (ISBN 9783031805066; 9783031805073) (ISSN 0302-9743)
DOI 2025,
Articolo in Atti di convegno - Scheda ARCA: 10278/5090329
Bicciato, Alessandro; Cosmo, Luca; Minello, Giorgia; Rossi, Luca; Torsello, Andrea GNN-LoFI: A novel graph neural network through localized feature-based histogram intersection in PATTERN RECOGNITION, vol. 148 (ISSN 0031-3203)
DOI 2024,
Articolo su rivista - Scheda ARCA: 10278/5062361
Cosmo, Luca; Minello, Giorgia; Bicciato, Alessandro; Bronstein, Michael M.; Rodolà, Emanuele; Rossi, Luca; Torsello, Andrea Graph Kernel Neural Networks in IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. PP, pp. 1-14 (ISSN 2162-237X)
DOI 2024,
Articolo su rivista - Scheda ARCA: 10278/5062362
Bicciato, A; Cosmo, L; Minello, G; Rossi, L; Torsello, A Classifying Me Softly: A Novel Graph Neural Network Based on Features Soft-Alignment , Structural, Syntactic, and Statistical Pattern Recognition, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, SPRINGER INTERNATIONAL PUBLISHING AG, vol. 13813, pp. 43-53, Convegno: S+SSPR 2022 (ISBN 978-3-031-23027-1; 978-3-031-23028-8) (ISSN 0302-9743)
DOI 2022,
Articolo in Atti di convegno - Scheda ARCA: 10278/5018602