3 papers
cs.LG2026
Converse and Collision-Based Achievability for Node Localization with Hybrid Distance-Spectral Graph Positional Encodings
Zimo Yan, Yifan Li, Hao Li +4
Graph positional encodings are widely used in graph neural networks and graph Transformers, yet it remains unclear when the code itself can identify nodes. We study a hybrid distan…
cs.LG2025
Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
Zimo Yan, Zheng Xie, Chang Liu +1
Message passing graph neural networks are widely used for learning on graphs, yet their expressive power is limited by the one-dimensional Weisfeiler-Lehman test and can fail to di…
cs.SI2025
Higher-order Network phenomena of cascading failures in resilient cities
Jinghua Song, Yuan Wang, Zimo Yan
Modern urban resilience is threatened by cascading failures in multimodal transport networks, where localized shocks trigger widespread paralysis. Existing models, limited by their…