This directory contains code necessary to run the GraphSage algorithm. GraphSage can be viewed as a stochastic generalization of graph convolutions, and it is especially useful for massive, dynamic ...

Abstract: The scalability of graph neural networks (GNNs) is critically dependent on the efficiency of their sampling and feature aggregation steps, which are often bottlenecked by memory access ...

MotivationAccurate drug–target interaction (DTI) prediction remains difficult for underexplored drugs and targets, especially when available interaction evid ...

Abstract: Graph convolutional network (GCN) has shown potential in hyperspectral image (HSI) classification. However, GCN is a transductive learning method, which is difficult to aggregate the new ...