Author

Alessio Borgi

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#machine learning Oct 2026

Oscillatory Neural Dynamics over Sheaves

Effective long-range propagation remains a central challenge in graph neural networks, as increasing a model's propagation depth does not guarantee that distant nodes effectively influence each other. Sheaf neural networks enrich graph propagation through matrix-valued transport between stalks; still, this expressivity...

J. Van Looy, Alessandro Trenta, Alessio Gravina et al. · arXiv (Cornell University) · 0 citations

Review Open access Sep 2026

Program Graph Learning for Software Vulnerability Analysis: A Survey

Software vulnerabilities represent an enduring threat to modern cyberspace. Effective vulnerability detection increasingly relies on reasoning about complex program semantics, structural dependencies, and execution behaviors. Consequently, extracting vulnerability-relevant features from code efficiently has become a pr...

Jun-Jie Wang, Tong Yu, Ming Li et al. · Transactions on Graph Intell... · 0 citations

#artificial intelligence Preprint Aug 2026

Equivariant Sheaf Neural Networks: Learning Geometric Transport on Graphs

ESNN is introduced, an Equivariant Sheaf Neural Network that enriches this interaction by learning directed, matrix-valued transport between neighboring vector features while preserving exact Euclidean equivariance.

Alessio Borgi, M. Severino, Fabrizio Silvestri et al. · 0 citations