graph transformer networks
Graph transformer networks (GTNs) are a type of machine learning model that operate on graph-structured data. They aim to transform and refine the representation of graphs by incorporating both local and global information. GTNs are designed to learn and encode complex relationships between the nodes and edges of a graph, making them effective in tasks such as node classification, graph classification, and link prediction.
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