nguyentuc/implicit_graph_neural_networks

Implicit layer with GCNs

Implicit Graph Neural Networks

This repository is the official PyTorch implementation of "Implicit Graph Neural Networks".

Fangda Gu*, Heng Chang*, Wenwu Zhu, Somayeh Sojoudi, Laurent El Ghaoui. Implicit Graph Neural Networks, NeurIPS 2020.

New environments: cuda 11.4, pytorch 1.12

Install pytorch:

• conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch Install pytorch geometric:
• pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.0+cu113.html
• pip install torch-sparse -f https://data.pyg.org/whl/torch-1.12.0+cu113.html
• pip install torch-geometric Install scipy, numpy and networkx
• conda install -c conda-forge scipy
• conda install numpy
• conda install networkx

Tasks

There are two task nodeclassification and graphclassification.

Run node classification task

In the folder nodeclassification: python train_IGNN_{name_dataset}.py

Datasets

For Amazon dataset, please use the following dropbox link to download:

https://www.dropbox.com/sh/3gwr2wgh455q9pi/AAB0i6EQimVGslrqtsTIWsL0a?dl=0

Then put the amazon-all folder under the data folder.

Run node graph task

In the folder nodeclassification: python train_IGNN.py --dataset {name_dataset}