Qinji Shu

Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective

Size transfer scales Graph Convolutional Networks (GCNs) by applying models trained on sampled subgraphs to larger target graphs. However, existing theoretical guarantees are typically confined to dense graphs or restricted sparsity regimes, failing to cover the arbitrary sparsity of real-world netw…