86 citations · 241 across the 12 of their papers we have counts for
4 papers · 1 filter
GRAND+: Scalable Graph Random Neural Networks
Wenzheng Feng, Yuxiao Dong, Tinglin Huang +4
Graph neural networks (GNNs) have been widely adopted for semi-supervised learning on graphs. A recent study shows that the graph random neural network (GRAND) model can generate s…
SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs
Xiao Liu, Haoyun Hong, Xinghao Wang +4
Entity alignment, aiming to identify equivalent entities across different knowledge graphs (KGs), is a fundamental problem for constructing Web-scale KGs. Over the course of its de…
On Event-Driven Knowledge Graph Completion in Digital Factories
Martin Ringsquandl, Evgeny Kharlamov, Daria Stepanova +4
Smart factories are equipped with machines that can sense their manufacturing environments, interact with each other, and control production processes. Smooth operation of such fac…
TDGIA:Effective Injection Attacks on Graph Neural Networks
Xu Zou, Qinkai Zheng, Yuxiao Dong +4
Graph Neural Networks (GNNs) have achieved promising performance in various real-world applications. However, recent studies have shown that GNNs are vulnerable to adversarial atta…