This example shows how to use geometric deep learning models defined in dgl.nn.pytorch.conv
for
graph classification.
Currently we support following models:
By transforming images to graphs, graph classifcation algorithms could be applied to image classification problems.
python mnist.py --model cheb --gpu 0
python mnist.py --model monet --gpu 0
We thank Xavier Bresson for providing
code for graph coarsening algorithm and grid graph building in
CE7454_2019 Labs.