Dual-view graph-of-graph representation learning with graph Transformer for graph-level anomaly detection

This paper proposes a novel approach called Dual-View Graph-of-Graph Representation Learning Network for unsupervised GLAD, which takes into account both intra-graph and inter-graph perspectives, and devise a Graph-of-Graph-based dual-view representation learning network to explicitly capture cross-graph interdependencies.