most citedExtending the RANGE of Graph Neural Networks: Relaying Attention Nodes for Global Encoding

6 citations · 6 across the 1 of their papers we have counts for

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physics.comp-ph2025★ 6 cited

Extending the RANGE of Graph Neural Networks: Relaying Attention Nodes for Global Encoding

Alessandro Caruso, Jacopo Venturin, Lorenzo Giambagli +3

Graph Neural Networks (GNNs) are routinely used in molecular physics, social sciences, and economics to model many-body interactions in graph-like systems. However, GNNs are inhere…