CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs

Graph Visualization, also known as Graph Drawing, aims to find geometric embeddings of graphs that optimize certain criteria. Stress is a widely used metric; stress is minimized when every pair of nodes is positioned at their shortest path distance. However, stress optimization presents computational challenges due to its inherent complexity and is usually solved using heuristics in practice. We introduce a scalable Graph Neural Network (GNN) based Graph Drawing framework with sub-quadratic runtime that can learn to optimize stress. Inspired …

challenges complexity computational core cs.cg cs.lg embeddings every framework gnns graph graphs hierarchical nodes optimization path scalable stress visualization