Graph Contrastive Learning with Augmentations (Appendix) Yuning You

Superpixel graphs (statistics in Table S1) gain from all augmentations except attribute masking as shown in Figure S1. D Difficulty of Contrastive T asks v.s. Pairing "Identical" stands for a no-augmentation baseline for contrastive The baseline training-from-scratch accuracy is 79.71%. Performance on contrastive learning with different implemented subgraph. For subgraph, we propose the following variants with difficulty levels.