“…Graph Attention Networks (GATs) have been successfully applied to various tasks over graphs (Velickovic et al, 2018;Lee et al, 2018b), such as graph classification (Wu et al, 2019b;Lee et al, 2018a), link prediction (Abu-El-Haija et al, 2018), and node classification (Lee et al, 2019;Zhang et al, 2020a). GATs learn from the underlying graph structure by making use of localized attention mechanism (Wu et al, 2019a;Xu et al, 2019;Vashishth et al, 2020b), where the hidden representation of each node is computed by recursively aggregating and attending over its corresponding local neighbors' features, and the weighting coefficients are calculated inductively with self-attention strategy (Thekumparampil et al, 2018;Qian et al, 2018;Zhang et al, 2018).…”