BOCCHI, GIOVANNI
BOCCHI, GIOVANNI
Dipartimento di Scienze e Politiche Ambientali
NETWORKS OF GROUP EQUIVARIANT NON-EXPANSIVE OPERATORS FOR ARTIFICIAL INTELLIGENCE. MODELS, APPLICATIONS AND INTERPRETABILITY.
2025 G. Bocchi
Prototypical Explanations in an AI Method for Protein Pocket Detection
2025 G. Bocchi, A. Micheletti, C. Gratteri, C. Talarico
A novel approach to graph distinction through GENEOs and permutants
2025 G. Bocchi, M. Ferri, P. Frosini
SCENE-Net: Geometric induction for interpretable and low-resource 3D pole detection with Group-Equivariant Non-Expansive Operators
2025 D. Lavado, A. Micheletti, G. Bocchi, P. Frosini, C. Soares
GENEOnet: statistical analysis supporting explainability and trustworthiness
2025 G. Bocchi, P. Frosini, A. Micheletti, A. Pedretti, C. Gratteri, F. Lunghini, A.R. Beccari, C. Talarico
GENEOnet: a breakthrough in protein binding pocket detection using group equivariant non-expansive operators
2025 G. Bocchi, P. Frosini, A. Micheletti, A. Pedretti, G. Palermo, D. Gadioli, C. Gratteri, F. Lunghini, A.D. Biswas, P.F.W. Stouten, A.R. Beccari, A. Fava, C. Talarico
A geometric XAI approach to protein pocket detection
2024 G. Bocchi, P. Frosini, A. Micheletti, A. Pedretti, G. Palermo, D. Gadioli, C. Gratteri, F. Lunghini, A.R. Beccari, A. Fava, C. Talarico
A new paradigm for Artificial Intelligence based on Group Equivariant Non-Expansive Operators (GENEOs) applied to protein pocket detection
2023 G. Bocchi, A. Micheletti, P. Frosini, A. Pedretti, C. Gratteri, F. Lunghini, A.R. Beccari, C. Talarico
On the finite representation of linear group equivariant operators via permutant measures
2023 G. Bocchi, S. Botteghi, M. Brasini, P. Frosini, N. Quercioli
Explainable Machine Learning based on Group Equivariant Non-Expansive Operators (GENEOs). Protein pocket detection: a case study
2023 G. Bocchi, A. Micheletti, P. Frosini, A. Pedretti, A.R. Beccari, F. Lunghini, C. Talarico, C. Gratteri