6 citations · 10 across the 3 of their papers we have counts for
4 papers · 1 filter
Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks
Jiahao Liu, Guixiang Ma, Fei Jiang +3
Brain networks have received considerable attention given the critical significance for understanding human brain organization, for investigating neurological disorders and for cli…
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis
Ye Liu, Lifang He, Bokai Cao +3
Network analysis of human brain connectivity is critically important for understanding brain function and disease states. Embedding a brain network as a whole graph instance into a…
Multi-view Graph Embedding with Hub Detection for Brain Network Analysis
Guixiang Ma, Chun-Ta Lu, Lifang He +2
Multi-view graph embedding has become a widely studied problem in the area of graph learning. Most of the existing works on multi-view graph embedding aim to find a shared common n…
Discriminative Feature Selection for Uncertain Graph Classification
Xiangnan Kong, Philip S. Yu, Xue Wang +1
Mining discriminative features for graph data has attracted much attention in recent years due to its important role in constructing graph classifiers, generating graph indices, et…