5 citations · 13 across the 5 of their papers we have counts for
5 papers
Discriminatively Constrained Semi-supervised Multi-view Nonnegative Matrix Factorization with Graph Regularization
Guosheng Cui, Ruxin Wang, Dan Wu +1
In recent years, semi-supervised multi-view nonnegative matrix factorization (MVNMF) algorithms have achieved promising performances for multi-view clustering. While most of semi-s…
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.…
HopGAT: Hop-aware Supervision Graph Attention Networks for Sparsely Labeled Graphs
Chaojie Ji, Ruxin Wang, Rongxiang Zhu +2
Due to the cost of labeling nodes, classifying a node in a sparsely labeled graph while maintaining the prediction accuracy deserves attention. The key point is how the algorithm l…