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cs.LG2026
Graph Hierarchical Recurrence for Long-Range Generalization
Stefano Carotti, Marco Pacini, Alessio Gravina +3
Graph Neural Networks (GNNs) and Graph Transformers (GTs) are now a fundamental paradigm for graph learning, combining the representation-learning capabilities of deep models with…
cs.LG2024
Multi-Relational Graph Neural Network for Out-of-Domain Link Prediction
Asma Sattar, Georgios Deligiorgis, Marco Trincavelli +1
Dynamic multi-relational graphs are an expressive relational representation for data enclosing entities and relations of different types, and where relationships are allowed to var…