3 papers
cs.LG2025
HeRB: Heterophily-Resolved Structure Balancer for Graph Neural Networks
Ke-Jia Chen, Wenhui Mu, Zheng Liu
Recent research has witnessed the remarkable progress of Graph Neural Networks (GNNs) in the realm of graph data representation. However, GNNs still encounter the challenge of stru…
cs.LG2025
HeGMN: Heterogeneous Graph Matching Network for Learning Graph Similarity
Shilong Sang, Ke-Jia Chen, Zheng liu
Graph similarity learning (GSL), also referred to as graph matching in many scenarios, is a fundamental problem in computer vision, pattern recognition, and graph learning. However…
cs.SI2023
Balancing Augmentation with Edge-Utility Filter for Signed GNNs
Ke-Jia Chen, Yaming Ji, Youran Qu +1
Signed graph neural networks (SGNNs) has recently drawn more attention as many real-world networks are signed networks containing two types of edges: positive and negative. The exi…