9 citations · 16 across the 4 of their papers we have counts for
4 papers
Rubik: A Hierarchical Architecture for Efficient Graph Learning
Xiaobing Chen, Yuke Wang, Xinfeng Xie +9
Graph convolutional network (GCN) emerges as a promising direction to learn the inductive representation in graph data commonly used in widespread applications, such as E-commerce,…
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks
Boyuan Feng, Yuke Wang, Zheng Wang +1
With the increasing popularity of graph-based learning, graph neural networks (GNNs) emerge as the essential tool for gaining insights from graphs. However, unlike the conventional…
Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers
Boyuan Feng, Yuke Wang, Xu Li +1
Graph neural networks (GNNs) have achieved high performance in analyzing graph-structured data and have been widely deployed in safety-critical areas, such as finance and autonomou…
SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization
Boyuan Feng, Yuke Wang, Xu Li +3
With the increasing popularity of graph-based learning, Graph Neural Networks (GNNs) win lots of attention from the research and industry field because of their high accuracy. Howe…