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Existing Graph Neural Network (GNN) methods that learn inductive unsupervised graph representations focus on learning node and edge representations by predicting observed edges in the graph.
Hypergraph convolution and hypergraph attention
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Relational pooling for graph representations
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Deep Graph Infomax
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How powerful are graph neural networks?
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Weisfeiler and leman go sparse: Towards scalable higher-order graph embeddings
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Negative sampling for hyperlink prediction in networks
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