Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning

Yuankai Luo, Hongkang Li, Qijiong Liu +2

We present a novel end-to-end framework that generates highly compact (typically 6-15 dimensions), discrete (int4 type), and interpretable node representations, termed node identif…