Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains
Published in International Conference on Machine Learning (ICML), 2025
This paper propose SYNC, a novel method for evolving domain generalization that learns time-aware causal representations by modeling dynamic causal factors and mechanism drifts, achieving robust generalization across temporal domains.