Björn Kampa

A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings

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 distance between graphs. Our idea is to derive representations of graphs as Gaussian mixture models, fitted to distributi…