Scalable and Expressive Graph Representation Learning with Temporal, Structural, and Zero-Shot Capabilities

Graph representation learning has emerged as a foundational discipline within modern data science, essential for modeling the complex relational systems ubiquitous in domains from social networks to bioinformatics. However, conventional approaches, particularly Graph Neural Networks (GNN), exhibit s