2021
Adversarial Graph Augmentation to Improve Graph Contrastive Learning
NeurIPS 2021poster
Self-supervised learning of graph neural networks (GNN) is in great need because of the widespread label scarcity issue in real-world graph/network data. Graph contrastive learning (GCL), by training GNNs to maximize the correspondence between the representations of the same graph in its different a…