3260 papers • 126 benchmarks • 313 datasets
Graph Classification is a task that involves classifying a graph-structured data into different classes or categories. Graphs are a powerful way to represent relationships and interactions between different entities, and graph classification can be applied to a wide range of applications, such as social network analysis, bioinformatics, and recommendation systems. In graph classification, the input is a graph, and the goal is to learn a classifier that can accurately predict the class of the graph. ( Image credit: Hierarchical Graph Pooling with Structure Learning )
(Image credit: Open Source)
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