Few-Shot Learning on Graphs: Meta-learning, Pre-training, and Hybrid Approaches

The author explores the advancements in few-shot learning on graphs through meta-learning, pre-training, and hybrid approaches to address the challenge of limited labeled data availability. The survey categorizes existing studies into three major families and outlines future research directions.