Definition
Identity-aware GNN (ID-GNN) is designed to compute structure-aware Node Embedding.
Architecture
Across all example tasks, traditional GNN will always assign the same embedding to both nodes, edges and graphs, because for all tasks the computational graphs are identical. In contrast, the colored computational graphs provided by ID-GNN allow for clear differentiation between the nodes of label A and label B, as the colored computational graphs are no longer identical across the tasks.
Heterogeneous Message Passing
ID-GNN implies inductive-node coloring by applying different message/aggregation to nodes with different colorings.
To embed a node , extract -centered local network (ego network) and assign a unique coloring to the central node of the network. The message passing and aggregation differ by the node’s coloring.
ID-GNN-Fast
The ID-GNN model can be simplified by just adding the cycle count at each level as an augmented node feature without using the two different networks.