Projects

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.

PhD First Year Project – We introduce the concept of hybrid graphs, a unified definition for higher-order graphs, and present the Hybrid Graph Benchmark (HGB), a collection of hybrid graph datasets with an extensible evaluation framework.