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cs.LG2025
A Unified Invariant Learning Framework for Graph Classification
Yongduo Sui, Jie Sun, Shuyao Wang +4
Invariant learning demonstrates substantial potential for enhancing the generalization of graph neural networks (GNNs) with out-of-distribution (OOD) data. It aims to recognize sta…
cs.LG2023★ 2 cited
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs
Xingtong Yu, Zhenghao Liu, Yuan Fang +3
Graph neural networks have emerged as a powerful tool for graph representation learning, but their performance heavily relies on abundant task-specific supervision. To reduce label…