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Discovering latent node Information by graph attention network
2021
Scientific Reports
AbstractIn this paper, we propose graph attention based network representation (GANR) which utilizes the graph attention architecture and takes graph structure as the supervised learning information. Compared with node classification based representations, GANR can be used to learn representation for any given graph. GANR is not only capable of learning high quality node representations that achieve a competitive performance on link prediction, network visualization and node classification but
doi:10.1038/s41598-021-85826-x
pmid:33772048
fatcat:6p33zekhljd73awn62hjhhjyza