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Empowering Graph Neural Networks for Long-Range Learning on Graphs
Graphs are pervasive in various fields, including social networks, biological interactomes, transportation networks, and more. Understanding these graphs through structured representations is crucial for grasping their complex topologies and interdependencies, which are vital for numerous applications within these domains. In recent years, Graph Neural Networks (GNNs) have attracted considerable attention and shown promising results in... Read more