Graph augmentation for node-level few-shot learning

Zongqian Wu, Peng Zhou, Junbo Ma, Jilian Zhang, Guoqin Yuan, Xiaofeng Zhu

Abstract: Highlights•We use data augmentation and GCN with optimized initialization for efficiency.•The parameter initialization module aims to improve generalization and efficiency.•The proposed support and shot augmentation modules aim to mine rich information.