3 papers
cs.LG2026
Topology-induced Operators Reveal Complementary Graph Representations without Training
Meng Qin, Jinqiang Cui, Hongwei Zheng +2
Graph representation learning has largely focused on designing increasingly sophisticated models to transform graph topology into vector representations, or embeddings. However, th…
cs.LG2025
InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections
Meng Qin, Weihua Li, Jinqiang Cui +1
Graph partitioning (GP), a.k.a. community detection, is a classic problem that divides nodes of a graph into densely-connected blocks. From a perspective of graph signal processing…
cs.LG2025
Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature Aggregation
Meng Qin, Jiahong Liu, Irwin King
Graph neural networks (GNNs), which capture graph structures via a feature aggregation mechanism following the graph embedding framework, have demonstrated a powerful ability to su…