Graph Attention Network
The Graph Attention Network (GAT), introduced by Veličković and colleagues in 2018, is a graph neural network variant that learns how much importance to assign to each neighbouring node through a self-attention mechanism. On heterogeneous neighbourhoods and relational classification it produces results superior to graph convolutional networks (GCN).
Rekodi ya chanzo
Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.
- Veličković, P. et al. (2018). Graph Attention Networks. ICLR. · URL
- Brody, S. et al. (2022). How Attentive are Graph Attention Networks? ICLR. · URL
Madai yaliyotunzwa
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Mbinu zinazohusiana
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