Machine learning

图注意力网络

图注意力网络（GAT）由 Veličković 等人在 2018 年提出，是一种图神经网络变体，它通过自注意力机制学习为每个邻居节点分配多少重要性。在异构邻域和关系分类方面，它产生的优于图卷积网络（GCN）。

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The neighbourhood of related methods — select a node to explore.

图注意力网络

Veličković, P. et al. (2018). Graph Attention Networks. ICLR. link ↗
Brody, S. et al. (2022). How Attentive are Graph Attention Networks? ICLR. link ↗

ScholarGate. (2026, June 1). Graph Attention Network (GAT). ScholarGate. https://scholargate.app/zh/deep-learning/graph-attention-network

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.