12 citations · 36 across the 8 of their papers we have counts for
8 papers
Node Injection Attack Based on Label Propagation Against Graph Neural Network
Peican Zhu, Zechen Pan, Keke Tang +3
Graph Neural Network (GNN) has achieved remarkable success in various graph learning tasks, such as node classification, link prediction and graph classification. The key to the su…
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry
Zeyu Wang, Tianyi Jiang, Jinhuan Wang +1
Molecular property prediction refers to the task of labeling molecules with some biochemical properties, playing a pivotal role in the drug discovery and design process. Recently,…
Subgraph Networks Based Contrastive Learning
Jinhuan Wang, Jiafei Shao, Zeyu Wang +3
Graph contrastive learning (GCL), as a self-supervised learning method, can solve the problem of annotated data scarcity. It mines explicit features in unannotated graphs to genera…
Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning
Dayuan Chen, Jian Zhang, Yuqian Lv +5
Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbat…
Targeted k-node Collapse Problem: Towards Understanding the Robustness of Local k-core Structure
Yuqian Lv, Bo Zhou, Jinhuan Wang +1
The concept of k-core, which indicates the largest induced subgraph where each node has k or more neighbors, plays a significant role in measuring the cohesiveness and the engageme…
TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum
Jinhuan Wang, Pengtao Chen, Xinyao Xu +4
Due to the decentralized and public nature of the Blockchain ecosystem, the malicious activities on the Ethereum platform impose immeasurable losses for the users. Existing phishin…
Null Model-Based Data Augmentation for Graph Classification
Qi Xuan, Zeyu Wang, Jinhuan Wang +3
In network science, the null model is typically used to generate a series of graphs based on randomization as a term of comparison to verify whether a network in question displays…
COREATTACK: Breaking Up the Core Structure of Graphs
Bo Zhou, Yuqian Lv, Jinhuan Wang +2
The concept of k-core in complex networks plays a key role in many applications, e.g., understanding the global structure, or identifying central/critical nodes, of a network. A ma…