2026
Fast Mixture of Curvature-Aware Experts for Diverse and Dynamic Graph Topologies
ICML 2026poster
Dynamic graph learning, which focuses on modeling the merging, vanishing, and reconnection of nodes and edges, is crucial for real-world applications. In dynamic graphs, node neighborhoods often exhibit diverse and time-evolving topologies, including hierarchical, grid-like, and cyclic patterns. Exi…