26 citations · 50 across the 2 of their papers we have counts for
4 papers
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
Cunchao Zhu, Muhao Chen, Changjun Fan +2
Large knowledge graphs often grow to store temporal facts that model the dynamic relations or interactions of entities along the timeline. Since such temporal knowledge graphs ofte…
Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
Xuelu Chen, Muhao Chen, Changjun Fan +3
Predicting missing facts in a knowledge graph (KG) is a crucial task in knowledge base construction and reasoning, and it has been the subject of much research in recent works usin…
Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
Ziniu Hu, Changjun Fan, Ting Chen +2
Graph neural networks (GNNs) are shown to be successful in modeling applications with graph structures. However, training an accurate GNN model requires a large collection of label…
Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach
Changjun Fan, Li Zeng, Yuhui Ding +3
Betweenness centrality (BC) is one of the most used centrality measures for network analysis, which seeks to describe the importance of nodes in a network in terms of the fraction…