Conference
Open access
Sep 2026
Mitigating Dynamic Graph Distribution Shifts via Spectral Augmentation
This paper proposes a spectral-based graph augmentation framework designed to investigate and improve generalization behavior in dynamic graphs under distribution shifts and develops a multi-encoder architecture in which each encoder targets a specific spectral shift component to generate referential representations.
Qian-Yu Song, Chao Li, Zhongying Zhao et al.
· Proceedings of the Thirty-Fi... · 0 citations