DataFunTalk

Jan 2, 2022 · Artificial Intelligence

Understanding the Expressive Power of Graph Neural Networks and Advanced Models

This article reviews the theoretical foundations of graph neural networks, evaluates their expressive capabilities through tasks such as distinguishing non‑isomorphic graphs, subgraph counting, and attributed walk counting, and introduces stronger models like Ring‑GNN, Local Relational Pooling, and Graph‑Augmented MLP with experimental results on molecular prediction.