75 citations · 83 across the 4 of their papers we have counts for
4 papers
Mask-GVAE: Blind Denoising Graphs via Partition
Jia Li, Mengzhou Liu, Honglei Zhang +4
We present Mask-GVAE, a variational generative model for blind denoising large discrete graphs, in which "blind denoising" means we don't require any supervision from clean graphs.…
Adversarial Attack on Community Detection by Hiding Individuals
Jia Li, Honglei Zhang, Zhichao Han +3
It has been demonstrated that adversarial graphs, i.e., graphs with imperceptible perturbations added, can cause deep graph models to fail on node/graph classification tasks. In th…
Predicting Path Failure In Time-Evolving Graphs
Jia Li, Zhichao Han, Hong Cheng +4
In this paper we use a time-evolving graph which consists of a sequence of graph snapshots over time to model many real-world networks. We study the path classification problem in…
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Jia Li, Yu Rong, Hong Cheng +3
Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph u…