Graph Generative Methods

Imperial UROP 2023 Student Project – We propose an approach to improve GNN-based graph generative models including GCPN, GraphAF and GraphEBM, and investigate the correlation between GNN expressiveness in the graph prediction and graph generation contexts.

Imperial UROP 2023 Student Project – We propose an approach to improve GNN-based graph generative models including GCPN, GraphAF and GraphEBM, and investigate the correlation between GNN expressiveness in the graph prediction and graph generation contexts.

We propose an approach to improve GNN-based graph generative models including GCPN, GraphAF and GraphEBM, and investigate the correlation between GNN expressiveness in the graph prediction and graph generation contexts.