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This challenge has motivated many graph classification algorithms in recent years. Given a set of training graphs, each associated with a class label, graph classification aims to learn a model from ...

This repository contains datasets to quickly test graph classification algorithms, such as Graph Kernels and Graph Neural Networks. The purpose of this dataset is to make the features on the nodes and ...

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However, real structures represented by graphs are often of varying sizes, leading to the low accuracy of traditional graph classification methods. These graphs are called cross-scale graphs. To ...

Abstract: Automatic modulation classification (AMC) is a promising technology to realize intelligent wireless ... To solve these problems, we propose for the first time a modulation knowledge graph ...