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cs.LG2025
Directional Sheaf Hypergraph Networks: Unifying Learning on Directed and Undirected Hypergraphs
Emanuele Mule, Stefano Fiorini, Antonio Purificato +3
Hypergraphs provide a natural way to represent higher-order interactions among multiple entities. While undirected hypergraphs have been extensively studied, the case of directed h…
cs.LG2025
Adversarial training with restricted data manipulation
David Benfield, Stefano Coniglio, Phan Tu Vuong +1
Adversarial machine learning concerns situations in which learners face attacks from active adversaries. Such scenarios arise in applications such as spam email filtering, malware…
cs.LG2025
Sheaves Reloaded: A Directional Awakening
Stefano Fiorini, Hakan Aktas, Iulia Duta +4
Sheaf Neural Networks (SNNs) represent a powerful generalization of Graph Neural Networks (GNNs) that significantly improve our ability to model complex relational data. While dire…