AlphaGalileo4d
D2-GCN: a graph convolutional network with dynamic disentanglement for node classification
Disclaimer: AlphaGalileo is not responsible for the accuracy of news releases posted to AlphaGalileo by contributing ...
IEEE12d
KNIGCN: Key Node Identification in UAV Swarm Networks with Graph Convolution Networks
To solve this problem, a key node identification model based on Graph Convolutional Networks (GCN), named KNIGCN, is proposed. Specifically, the topology model of UAV cluster network is firstly built ...
IEEE27d
sigRGCN: A robust residual graph convolutional network for scRNA-seq data clustering
Recently, graph convolutional networks (GCNs) have gained prominence in scRNA-seq data clustering because they effectively learn cell representations by capturing the relationship between cells.
GitHub25d
Graph Convolutional Networks
This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of nodes in a graph, as described in our paper: Thomas N. Kipf, Max Welling, ...
GitHub20d
Towards Robust Cardiac Segmentation Using Graph Convolutional Networks
This repository is the source code for the training framework of Toward Robust Cardiac Segmentation Using Graph Convolutional Networks. Fully automatic cardiac segmentation can be a fast and ...