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, ...
Abstract: Graph matching aims to establish node correspondences between graphs, which is a classic combinatorial optimization problem. In recent years, (deep) learning-based methods have emerged as a ...
During the preview we may make changes to the API, and other mechanisms of this library, which you will be required to take along with bug fixes or feature improvements. This may impact your ...
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