2017
Learning Graph Representations with Embedding Propagation
NeurIPS 2017poster
We propose EP, Embedding Propagation, an unsupervised learning framework for graph-structured data. EP learns vector representations of graphs by passing two types of messages between neighboring nodes. Forward messages consist of label representations such as representations of words and other attr…