100 citations · 212 across the 12 of their papers we have counts for
4 papers · 1 filter
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond
Yifei Zhang, Hao Zhu, Zixing Song +2
Although augmentations (e.g., perturbation of graph edges, image crops) boost the efficiency of Contrastive Learning (CL), feature level augmentation is another plausible, compleme…
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
Yifei Zhang, Hao Zhu, Zixing Song +2
Graph contrastive learning (GCL) improves graph representation learning, leading to SOTA on various downstream tasks. The graph augmentation step is a vital but scarcely studied st…
Graph Component Contrastive Learning for Concept Relatedness Estimation
Yueen Ma, Zixing Song, Xuming Hu +3
Concept relatedness estimation (CRE) aims to determine whether two given concepts are related. Existing methods only consider the pairwise relationship between concepts, while over…
Graph-adaptive Rectified Linear Unit for Graph Neural Networks
Yifei Zhang, Hao Zhu, Ziqiao Meng +2
Graph Neural Networks (GNNs) have achieved remarkable success by extending traditional convolution to learning on non-Euclidean data. The key to the GNNs is adopting the neural mes…