Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning

Understand

Recently, there has been great success in applying deep neural networks on graph structured data.

• Most work, however, focuses on either node- or graph-level supervised learning, such as node, link or graph classification or node-level unsupervised learning (e.g.
• node clustering).
• Despite its wide range of possible applications, graph-level unsupervised learning has not received much attention yet.