Representation Learning and Reasoning with Graph Neural Networks

Graph Neural Networks (GNNs) are a powerful framework revolutionizing graph representation learning, but our understanding of their representational properties is limited. This project aims to explore the theoretical foundations of learning with graphs and relations in AI via the GNN architecture.