方法证据记录
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).
源记录
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Graph Attention Network (GAT)
分类方法记录 · ml-model / deep-learning
- Veličković, P. et al. (2018). Graph Attention Networks. ICLR. · URL
- Brody, S. et al. (2022). How Attentive are Graph Attention Networks? ICLR. · URL
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