SUCRe: Selective Uncertainty-Aware Contrastive Representation for Graph Transfer Learning
This work introduces structure-aware entropy-based matching discrepancy, which jointly models feature uncertainty and structural coherence to ensure accurate feature adaptation between graphs and develops a domain-aware semi-hard negative sampling strategy that constructs informative contrastive sets by filtering unrel...