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cs.LG2024
Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks
Yanwei Yue, Guibin Zhang, Haoran Yang +1
Graph Neural Networks (GNNs) demonstrate superior performance in various graph learning tasks, yet their wider real-world application is hindered by the computational overhead when…
cs.LG2024
IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs
Haoran Yang, Xiaobing Pei, Kai Yuan
Due to the performance degradation of graph neural networks (GNNs) under distribution shifts, the work on out-of-distribution (OOD) generalization on graphs has received widespread…
cs.LG2024
Hyperedge Interaction-aware Hypergraph Neural Network
Rongping Ye, Xiaobing Pei, Haoran Yang +1
Hypergraphs provide an effective modeling approach for modeling high-order relationships in many real-world datasets. To capture such complex relationships, several hypergraph neur…