Sheaf Neural Networks and biomedical applications

arXiv (Cornell University) 2026 Preprint Open access

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Authors: Aneeqa Mehrab, Jan Willem Van Looy, P. Demurtas, Stefano Iotti, Emil Malucelli, Francesca Romana Rossi, Ferdinando Zanchetta, R. Fioresi
DOI: 10.48550/arxiv.2602.00159
Cited by: 0

Abstract

The purpose of this paper is to elucidate the theory and mathematical modelling behind the sheaf neural network (SNN) algorithm and then show how SNN can effectively answer to biomedical questions in a concrete case study and outperform the most popular graph neural networks (GNNs) as graph convolutional networks (GCNs), graph attention networks (GAT) and GraphSage.

Fields of Study & Subjects

Advanced Graph Neural Networks Topological and Geometric Data Analysis Neural Networks and Applications

Publication details

Journal / source
arXiv (Cornell University)
Publication date
29 January 2026
Document type
Preprint