GATv2
Graph Attention Network v2
The __GATv2__ operator from the [“How Attentive are Graph Attention Networks?”](https://arxiv.org/abs/2105.14491) paper, which fixes the static attention problem of the standard [GAT](https://paperswithcode.com/method/gat) layer: since the linear layers in the standard GAT are applied right after each other, the ranking of attended nodes is unconditioned on the query node. In contrast, in GATv2, every node can attend to any other node.

GATv2 scoring function:

$e_{i,j} =\mathbf{a}^{\top}\mathrm{LeakyReLU}\left(\mathbf{W}[\mathbf{h}_i \, \Vert \,\mathbf{h}_j]\right)$
How Attentive are Graph Attention Networks?
https://paperswithcode.com/paper/how-attentive-are-graph-attention-networks
How Attentive are Graph Attention Networks?