CoDCL combines counterfactual data augmentation with contrastive learning as a universal module to improve temporal link prediction in social networks.
Towards better dynamic graph learning: New archi- tecture and unified library.Advances in Neural Infor- mation Processing Systems, 36:67686–67700,
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CoDCL: Counterfactual-Inspired Augmentation Contrastive Learning for Temporal Link Prediction in Social Networks
CoDCL combines counterfactual data augmentation with contrastive learning as a universal module to improve temporal link prediction in social networks.