10 citations · 14 across the 7 of their papers we have counts for
5 papers · 1 filter
Robust Node Representation Learning via Graph Variational Diffusion Networks
Jun Zhuang, Mohammad Al Hasan
Node representation learning by using Graph Neural Networks (GNNs) has been widely explored. However, in recent years, compelling evidence has revealed that GNN-based node represen…
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation
Jun Zhuang, Mohammad Al Hasan
Node classification using Graph Neural Networks (GNNs) has been widely applied in various real-world scenarios. However, in recent years, compelling evidence emerges that the perfo…
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision
Jun Zhuang, Mohammad Al Hasan
In recent years, plentiful evidence illustrates that Graph Convolutional Networks (GCNs) achieve extraordinary accomplishments on the node classification task. However, GCNs may be…
Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks
Jun Zhuang, Mohammad Al Hasan
Supervised learning, while deployed in real-life scenarios, often encounters instances of unknown classes. Conventional algorithms for training a supervised learning model do not p…
Deperturbation of Online Social Networks via Bayesian Label Transition
Jun Zhuang, Mohammad Al Hasan
Online social networks (OSNs) classify users into different categories based on their online activities and interests, a task which is referred as a node classification task. Such…