111 citations · 176 across the 13 of their papers we have counts for
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cs.LG2024★ 13 cited
Dynamic Graph Unlearning: A General and Efficient Post-Processing Method via Gradient Transformation
He Zhang, Bang Wu, Xiangwen Yang +3
Dynamic graph neural networks (DGNNs) have emerged and been widely deployed in various web applications (e.g., Reddit) to serve users (e.g., personalized content delivery) due to t…
cs.LG2024★ 1 cited
GOODAT: Towards Test-time Graph Out-of-Distribution Detection
Luzhi Wang, Dongxiao He, He Zhang +5
Graph neural networks (GNNs) have found widespread application in modeling graph data across diverse domains. While GNNs excel in scenarios where the testing data shares the distri…