IEEE

GraNDe: Near-Data Processing Architecture With Adaptive Matrix Mapping for Graph Convolutional Networks

Abstract: Graph Convolutional Network (GCN) models have attracted attention given their high accuracy in interpreting graph data. One of the primary building blocks of a GCN model is aggregation, ...
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 ...