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cs.LG2026
Rethinking Graph Generalization through the Lens of Sharpness-Aware Minimization
Yang Qiu, Yixiong Zou, Jun Wang
Graph Neural Networks (GNNs) have achieved remarkable success across various graph-based tasks but remain highly sensitive to distribution shifts. In this work, we focus on a preva…
cs.LG2025
Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
Yang Qiu, Yixiong Zou, Jun Wang +3
Out-of-distribution generalization under distributional shifts remains a critical challenge for graph neural networks. Existing methods generally adopt the Invariant Risk Minimizat…
cs.LG2024
PAGE: Parametric Generative Explainer for Graph Neural Network
Yang Qiu, Wei Liu, Jun Wang +1
This article introduces PAGE, a parameterized generative interpretive framework. PAGE is capable of providing faithful explanations for any graph neural network without necessitati…