Abstract: R-convolution graph kernels are conventional methods for graph classification. They decompose graphs into substructures and aggregate all the substructure similarity as graph similarity.

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Impact Statement: R-convolution graph kernels compare graphs without taking into account the distributions of substructures within and across graphs, leading to inaccurate graph similarity.

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