activity
20222026
most citedGENEOnet: Statistical analysis supporting explainability and trustworthiness

5 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2026

The impact of abnormal temperatures on crop yields in Italy: a functional quantile regression approach

Giovanni Bocchi, Alessandra Micheletti, Paolo Nota +1

In this study, we apply functional regression analysis to identify the specific within-season periods during which temperature and precipitation anomalies most affect crop yields.…

cs.LG2025★ 5 cited

GENEOnet: Statistical analysis supporting explainability and trustworthiness

Giovanni Bocchi, Patrizio Frosini, Alessandra Micheletti +5

Group Equivariant Non-Expansive Operators (GENEOs) have emerged as mathematical tools for constructing networks for Machine Learning and Artificial Intelligence. Recent findings su…

cs.LG2024★ 5 cited

A novel approach to graph distinction through GENEOs and permutants

Giovanni Bocchi, Massimo Ferri, Patrizio Frosini

The theory of Group Equivariant Non-Expansive Operators (GENEOs) was initially developed in Topological Data Analysis for the geometric approximation of data observers, including t…

cs.CV2023

Low-Resource White-Box Semantic Segmentation of Supporting Towers on 3D Point Clouds via Signature Shape Identification

Diogo Lavado, Cláudia Soares, Alessandra Micheletti +4

Research in 3D semantic segmentation has been increasing performance metrics, like the IoU, by scaling model complexity and computational resources, leaving behind researchers and…

q-bio.BM2022★ 2 cited

GENEOnet: A new machine learning paradigm based on Group Equivariant Non-Expansive Operators. An application to protein pocket detection

Giovanni Bocchi, Patrizio Frosini, Alessandra Micheletti +5

Nowadays there is a big spotlight cast on the development of techniques of explainable machine learning. Here we introduce a new computational paradigm based on Group Equivariant N…