Graph neutral networks (GNN) are a prominent class of deep learning methods designed for tasks whose inputs are graphs. Many natural and social phenomena can be viewed as graphs that contain rich relation (link) information among elements (nodes). GNN focus on a unique non-Euclidean data structure for machine learning, performing tasks such as node classification, link prediction, and clusterin...
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