15 citations · 36 across the 5 of their papers we have counts for
5 papers
Neural Multi-network Diffusion towards Social Recommendation
Boxin Du, Lihui Liu, Jiejun Xu +2
Graph Neural Networks (GNNs) have been widely applied on a variety of real-world applications, such as social recommendation. However, existing GNN-based models on social recommend…
FairGen: Towards Fair Graph Generation
Lecheng Zheng, Dawei Zhou, Hanghang Tong +3
There have been tremendous efforts over the past decades dedicated to the generation of realistic graphs in a variety of domains, ranging from social networks to computer networks,…
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
Jun Wu, Jingrui He, Jiejun Xu
Graph data widely exist in many high-impact applications. Inspired by the success of deep learning in grid-structured data, graph neural network models have been proposed to learn…
Deep Adversarial Network Alignment
Tyler Derr, Hamid Karimi, Xiaorui Liu +2
Network alignment, in general, seeks to discover the hidden underlying correspondence between nodes across two (or more) networks when given their network structure. However, most…
Inferring the geographic focus of online documents from social media sharing patterns
Ryan Compton, Matthew S. Keegan, Jiejun Xu
Determining the geographic focus of digital media is an essential first step for modern geographic information retrieval. However, publicly-visible location annotations are remarka…