5 citations · 13 across the 7 of their papers we have counts for
7 papers
Spatio-Temporal Multi-step Prediction of Influenza Outbreaks
Jie Zhang, Kazumitsu Nawata, Hongyan Wu
Flu circulates all over the world. The worldwide infection places a substantial burden on people's health every year. Regardless of the characteristic of the worldwide circulation…
Dynamic Virtual Graph Significance Networks for Predicting Influenza
Jie Zhang, Pengfei Zhou, Hongyan Wu
Graph-structured data and their related algorithms have attracted significant attention in many fields, such as influenza prediction in public health. However, the variable influen…
Meta-Path-Free Representation Learning on Heterogeneous Networks
Jie Zhang, Jinru Ding, Suyuan Liu +1
Real-world networks and knowledge graphs are usually heterogeneous networks. Representation learning on heterogeneous networks is not only a popular but a pragmatic research field.…
Smoothness Sensor: Adaptive Smoothness-Transition Graph Convolutions for Attributed Graph Clustering
Chaojie Ji, Hongwei Chen, Ruxin Wang +2
Clustering techniques attempt to group objects with similar properties into a cluster. Clustering the nodes of an attributed graph, in which each node is associated with a set of f…
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization
Chaojie Ji, Yijia Zheng, Ruxin Wang +2
Molecular optimization, which transforms a given input molecule X into another Y with desirable properties, is essential in molecular drug discovery. The traditional translating ap…
Perturb More, Trap More: Understanding Behaviors of Graph Neural Networks
Chaojie Ji, Ruxin Wang, Hongyan Wu
While graph neural networks (GNNs) have shown a great potential in various tasks on graph, the lack of transparency has hindered understanding how GNNs arrived at its predictions.…