用于节点消歧的着色图神经网络

Dec, 2019

Coloring graph neural networks for node disambiguation

George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux

TL;DR本文通过引入颜色编码的方法，改进了消息传递神经网络（MPNNs）的表达能力，提出了一种使用颜色消除相同节点属性的图神经网络，名为Colored Local Iterative Procedure (CLIP)，证明该方法是连续函数的通用逼近器，并实验验证了CLIP能够捕捉传统MPNN无法区分的结构特征，并且在基准图分类数据集中表现最佳。

Abstract

In this paper, we show that a simple coloring scheme can improve, both theoretically and empirically, the expressive power of message passing neural networks(MPNNs). More specifically, we introduce a graph neural network called Colored Local Iterative Procedure (CLIP) that uses colors