Graph Contrastive Coding
Graph Contrastive Coding
**Graph Contrastive Coding** is a self-supervised graph neural network pre-training framework to capture the universal network topological properties across multiple networks. GCC's pre-training task is designed as subgraph instance discrimination in and across networks and leverages contrastive learning to empower graph neural networks to learn the intrinsic and transferable structural representations.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
https://paperswithcode.com/paper/gcc-graph-contrastive-coding-for-graph-neural
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training