11 citations · 12 across the 6 of their papers we have counts for
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cs.LG2023★ 11 cited
Causality and Independence Enhancement for Biased Node Classification
Guoxin Chen, Yongqing Wang, Fangda Guo +4
Most existing methods that address out-of-distribution (OOD) generalization for node classification on graphs primarily focus on a specific type of data biases, such as label selec…
cs.AI2023
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
Boshen Shi, Yongqing Wang, Fangda Guo +3
Graph domain adaptation models are widely adopted in cross-network learning tasks, with the aim of transferring labeling or structural knowledge. Currently, there mainly exist two…