Before revision: \ coli . Graph neural networks use a message passing framework to learn an embedding of a graph in a continuous space , either using network topology alone, or including additional node features.
After revision: \ coli . Graph neural networks map graph nodes into a low-dimensional vector space representation, and can be trained to preserve both the local graph structure and the similarity between node features.