IEEE

Investigating the Robustness of Graph Neural Networks to Data Drift: A Case Study on Financial Transaction Data

Abstract: The performance of machine learning models in real-world applications is often challenged by data drift, in which the statistical properties of the data evolve over time. This phenomenon is ...
IEEE

sigRGCN: A Robust Residual Graph Convolutional Network for scRNA-Seq Data Clustering

Abstract: Clustering is a crucial step in single-cell RNA sequencing (scRNA-seq) data analysis, facilitating the discovery of new cell types and the grouping of similar cells. Recently, graph ...