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Graph Pooling Functions

pooling.Rd

Aggregate node features to graph-level representations for graph classification. These functions reduce node embeddings within each graph to a single vector.

Usage

pool_global_add(x, batch = NULL, size = NULL)

pool_global_mean(x, batch = NULL, size = NULL)

pool_global_max(x, batch = NULL, size = NULL)

Arguments

x

Tensor. Node feature matrix with shape (total_nodes, features). Contains features for all nodes from all graphs stacked together.

batch

Tensor or NULL. Batch vector assigning each node to a graph. Values should be graph indices starting from 1 (e.g., c(1,1,2,2,2) for 2 graphs with 2 and 3 nodes). If NULL, treats all nodes as a single graph.

size

Integer or NULL. Number of graphs. Automatically calculated if NULL.

Value

Tensor with shape (num_graphs, features) containing graph-level embeddings.

Details

These functions implement different reduction strategies:

  • pool_global_add: Sum of node features per graph

  • pool_global_mean: Mean of node features per graph

  • pool_global_max: Element-wise maximum of node features per graph