20 citations · 21 across the 6 of their papers we have counts for
6 papers
Soft Graph Clustering for single-cell RNA Sequencing Data
Ping Xu, Pengfei Wang, Zhiyuan Ning +3
Clustering analysis is fundamental in single-cell RNA sequencing (scRNA-seq) data analysis for elucidating cellular heterogeneity and diversity. Recent graph-based scRNA-seq cluste…
Rethinking Graph Contrastive Learning through Relative Similarity Preservation
Zhiyuan Ning, Pengfei Wang, Ziyue Qiao +2
Graph contrastive learning (GCL) has achieved remarkable success by following the computer vision paradigm of preserving absolute similarity between augmented views. However, this…
scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
Ping Xu, Zhiyuan Ning, Pengjiang Li +5
Single-cell RNA sequencing (scRNA-seq) reveals cell heterogeneity, with cell clustering playing a key role in identifying cell types and marker genes. Recent advances, especially g…
A Comprehensive Survey on Data Augmentation
Zaitian Wang, Pengfei Wang, Kunpeng Liu +6
Data augmentation is a series of techniques that generate high-quality artificial data by manipulating existing data samples. By leveraging data augmentation techniques, AI models…
Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations
Qingqing Long, Zheng Fang, Chen Fang +3
Traffic flow forecasting is a fundamental research issue for transportation planning and management, which serves as a canonical and typical example of spatial-temporal predictions…
scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
Cong Li, Meng Xiao, Pengfei Wang +3
Despite the inherent limitations of existing Large Language Models in directly reading and interpreting single-cell omics data, they demonstrate significant potential and flexibili…