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Abstract: Graph convolutional networks (GCNs) can quickly and accurately learn graph representations and have shown powerful performance in many graph learning domains. Despite their effectiveness, ...

Mt-KaHyPar is a shared-memory algorithm for partitioning graphs and hypergraphs. The balanced (hyper)graph partitioning problem asks for a partition of the node set of a (hyper)graph into k disjoint ...

Abstract: A graph structure is a powerful mathematical abstraction, which can not only represent information about individuals but also capture the interactions between individuals for reasoning.