4 papers
Learning the Network of Graphs for Graph Neural Networks
Yixiang Shan, Jielong Yang, Xing Liu +3
Graph neural networks (GNNs) have achieved great success in many scenarios with graph-structured data. However, in many real applications, there are three issues when applying GNNs…
An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks
Jielong Yang, Wee Peng Tay
The problem of estimating event truths from conflicting agent opinions in a social network is investigated. An autoencoder learns the complex relationships between event truths, ag…
GFCN: A New Graph Convolutional Network Based on Parallel Flows
Feng Ji, Jielong Yang, Qiang Zhang +1
In view of the huge success of convolution neural networks (CNN) for image classification and object recognition, there have been attempts to generalize the method to general graph…
Using Social Network Information in Bayesian Truth Discovery
Jielong Yang, Junshan Wang, Wee Peng Tay
We investigate the problem of truth discovery based on opinions from multiple agents who may be unreliable or biased. We consider the case where agents' reliabilities or biases are…