Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, ...

Abstract: Graph neural networks provide a powerful frame-work for recommendation systems by capturing dependencies through message passing and modeling user-item interactions using an adjacency matrix ...

Abstract: Subgraph matching is a core primitive in graph analytics, yet it remains difficult to scale due to its combinatorial complexity and highly irregular memory access patterns. Despite decades ...