Node representation learning plays a critical role in learning over graphs. Specifically, the success of contrastive learning methods in unsupervised node representation learning has been demonstrated for various tasks, which has led to increase in attention towards the field. Despite the increasing popula...
We then detail two sophisticated counterfactual models, one based on causal graphs, and one based on transport theories. We show transport based models have several theoretical advantages over the competition as explanation frameworks for machine learning algorithms. Keywords: explainability; counterfactual ...