3 papers
cs.SI2025
On the Cross-type Homophily of Heterogeneous Graphs: Understanding and Unleashing
Zhen Tao, Ziyue Qiao, Chaoqi Chen +3
Homophily, the tendency of similar nodes to connect, is a fundamental phenomenon in network science and a critical factor in the performance of graph neural networks (GNNs). While…
cs.CV2024
Out-of-Distribution Detection with Prototypical Outlier Proxy
Mingrong Gong, Chaoqi Chen, Qingqiang Sun +2
Out-of-distribution (OOD) detection is a crucial task for deploying deep learning models in the wild. One of the major challenges is that well-trained deep models tend to perform o…
cs.LG2024
Single-View Graph Contrastive Learning with Soft Neighborhood Awareness
Qingqiang Sun, Chaoqi Chen, Ziyue Qiao +2
Most graph contrastive learning (GCL) methods heavily rely on cross-view contrast, thus facing several concomitant challenges, such as the complexity of designing effective augment…