3 papers
cs.LG2024
SEGMN: A Structure-Enhanced Graph Matching Network for Graph Similarity Learning
Wenjun Wang, Jiacheng Lu, Kejia Chen +2
Graph similarity computation (GSC) aims to quantify the similarity score between two graphs. Although recent GSC methods based on graph neural networks (GNNs) take advantage of int…
cs.LG2023
Structural Imbalance Aware Graph Augmentation Learning
Zulong Liu, Kejia-Chen, Zheng Liu
Graph machine learning (GML) has made great progress in node classification, link prediction, graph classification and so on. However, graphs in reality are often structurally imba…
cs.SI2022
Collaborative Bi-Aggregation for Directed Graph Embedding
Linsong Liu, Kejia Chen, Zheng Liu
Directed graphs model asymmetric relationships between nodes and research on directed graph embedding is of great significance in downstream graph analysis and inference. Learning…