AEGCN: An Autoencoder-Constrained Graph Convolutional Network
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DOI: 10.1016/j.neucom.2020.12.061
Abstract: We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node classification task on graph domains. As suggested by its name, the core of this model is a convolutional network operating… read more here.
Keywords: graph convolutional; convolutional network; autoencoder constrained; network ... See more keywords