Neighborhood Aggregation

The core GNN operation by which a node updates its representation by collecting information from its neighbors.

Neighborhood aggregation lies at the center of the distinctive computational logic of graph neural networks. Each node combines its own features with messages from its neighbors to form a more contextual representation. As this process repeats across layers, broader graph structure becomes learnable. A significant part of GNN performance depends on the choice of aggregation function.