7 citations · 7 across the 3 of their papers we have counts for
4 papers
Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification
Beini Xie, Heng Chang, Ziwei Zhang +5
Graph Neural Architecture Search (GNAS) has achieved superior performance on various graph-structured tasks. However, existing GNAS studies overlook the applications of GNAS in res…
Adversarially Robust Neural Architecture Search for Graph Neural Networks
Beini Xie, Heng Chang, Ziwei Zhang +5
Graph Neural Networks (GNNs) obtain tremendous success in modeling relational data. Still, they are prone to adversarial attacks, which are massive threats to applying GNNs to risk…
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification
Xin Wang, Heng Chang, Beini Xie +5
Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications. Despite the huge success in le…
AutoGL: A Library for Automated Graph Learning
Ziwei Zhang, Yijian Qin, Zeyang Zhang +11
Recent years have witnessed an upsurge in research interests and applications of machine learning on graphs. However, manually designing the optimal machine learning algorithms for…