3 citations · 7 across the 7 of their papers we have counts for
7 papers
FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
Xiangyu Dong, Xingyi Zhang, Sibo Wang
Graph-level anomaly detection (GAD) is critical in diverse domains such as drug discovery, yet high labeling costs and dataset imbalance hamper the performance of Graph Neural Netw…
Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection
Xiping Li, Xiangyu Dong, Xingyi Zhang +7
Graph Anomaly Detection (GAD) in heterogeneous networks presents unique challenges due to node and edge heterogeneity. Existing Graph Neural Network (GNN) methods primarily focus o…
Towards More Accurate Full-Atom Antibody Co-Design
Jiayang Wu, Xingyi Zhang, Xiangyu Dong +5
Antibody co-design represents a critical frontier in drug development, where accurate prediction of both 1D sequence and 3D structure of complementarity-determining regions (CDRs)…
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
Xiangyu Dong, Xingyi Zhang, Lei Chen +2
Node Anomaly Detection (NAD) has gained significant attention in the deep learning community due to its diverse applications in real-world scenarios. Existing NAD methods primarily…
SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection
Xiangyu Dong, Xingyi Zhang, Yanni Sun +3
The smoothing issue in graph learning leads to indistinguishable node representations, posing significant challenges for graph-related tasks. However, our experiments reveal that t…
Rumor Detection on Social Media with Reinforcement Learning-based Key Propagation Graph Generator
Yusong Zhang, Kun Xie, Xingyi Zhang +2
The spread of rumors on social media, particularly during significant events like the US elections and the COVID-19 pandemic, poses a serious threat to social stability and public…
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
Xiangyu Dong, Xingyi Zhang, Sibo Wang
Graph-level anomaly detection has gained significant attention as it finds applications in various domains, such as cancer diagnosis and enzyme prediction. However, existing method…