Abstract: Self-supervised graph embedding has emerged as a powerful paradigm for learning expressive node and graph representations without relying on real labels. Several recent self-supervised ...

Abstract: In this article, we develop generative models that generate embeddings for graph nodes while using only their initial features without any knowledge about their neighborhoods and connections ...