A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings

Michael Scholkemper, Damin Kühn, Gerion Nabbefeld +3

Distance measures between graphs are important primitives for a variety of learning tasks. In this work, we describe an unsupervised, optimal transport based approach to define a d…