1 citations · 1 across the 1 of their papers we have counts for
5 papers
GraphPI: Efficient Protein Inference with Graph Neural Networks
Zheng Ma, Jiazhen Chen, Lei Xin +1
The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite these strides, its application i…
Towards Multiple Missing Values-resistant Unsupervised Graph Anomaly Detection
Jiazhen Chen, Xiuqin Liang, Sichao Fu +2
Unsupervised graph anomaly detection (GAD) has received increasing attention in recent years, which aims to identify data anomalous patterns utilizing only unlabeled node informati…
Disentangling the Complex Multiplexed DIA Spectra in De Novo Peptide Sequencing
Zheng Ma, Zeping Mao, Ruixue Zhang +5
Data-Independent Acquisition (DIA) was introduced to improve sensitivity to cover all peptides in a range rather than only sampling high-intensity peaks as in Data-Dependent Acquis…
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs
Jiazhen Chen, Sichao Fu, Zheng Ma +3
Semi-supervised graph anomaly detection (GAD) has recently received increasing attention, which aims to distinguish anomalous patterns from graphs under the guidance of a moderate…
Towards Cross-domain Few-shot Graph Anomaly Detection
Jiazhen Chen, Sichao Fu, Zhibin Zhang +4
Few-shot graph anomaly detection (GAD) has recently garnered increasing attention, which aims to discern anomalous patterns among abundant unlabeled test nodes under the guidance o…