Our team member, Van Thuy Hoang, presented research outcomes for this year at the 2nd CUK Annual Colloquium on Artificial Intelligence (CUK AI Colloquium 2023). Also, we would like to extend our congratulations to Van Thuy Hoang for winning the Exellence in Research (EiR) Award. This recognition showcases his dedication and expertise in his research progress and future plans.
Van Thuy Hoang
- Topic: Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity
- Abstract: We present Unified Graph Transformer Networks (UGT) that effectively integrate local and global structural information into fixed-length vector representations. First, UGT learns local structure by identifying the local substructures and aggregating features of the k-hop neighborhoods of each node. Second, we construct virtual edges, bridging distant nodes with structural similarity to capture the long-range dependencies. Third, UGT learns unified representations through self-attention, encoding structural distance and p-step transition probability between node pairs. Furthermore, we propose a self-supervised learning task that effectively learns transition probability to fuse local and global structural features, which could then be transferred to other downstream tasks. Experimental results on 21 real-world benchmark datasets over various downstream tasks showed that UGT significantly outperformed baselines that consist of state-of-the-art models. In addition, UGT reaches the third-order Weisfeiler-Lehman power to distinguish non-isomorphic graph pairs.
