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Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
The SEMB library is an easy-to-use tool for getting and evaluating structural node embeddings in graphs.
How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)
Select a set of pairs to check in link prediction from the vast, sparse space of possible pairs
Representation learning-based graph alignment based on implicit matrix factorization and structural embeddings
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