A Method for Node Classification in Random Trees Using Graph Neural Networks and Markov Networks

A method is proposed to model the joint probability distribution over node labels in random trees using a Markov Network parameterized by a Graph Neural Network. This allows for capturing dependencies between node labels and outperforms baseline methods on a sentiment analysis dataset.