AutomorphicEquivalence-aware GraphNeuralNetwork

However, existing graph neural networks (GNNs) fail to capture such an important property. To make GNN aware of automorphic equivalence, we first introduce a localized variant of this concept -- ego-centered automorphic equivalence (Ego-AE). Then, we design a novel variant of GNN,i.e., GRAPE, that uses learnable AE-aware aggregators to explicitly differentiate the Ego-AE ofeachnode'sneighbors withtheaidsofvarious subgraph templates.