Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The repository is organised as follows:
data/
contains datasets Cora, Cora-ML, Citeseer, Pubmed, Amazon Computers, and Amazon Photo;new_data/
contains datasets Chameleon and Squirrel;models/
contains the implementation of the GND-Nets (gndnets_slp.py
,gndnets_mlp.py
, andgndnets_ds.py
);utils/
contains:- an implementation of three variants of graph neural diffusions (
layers.py
); - preprocessing subroutines (
process.py
);
- an implementation of three variants of graph neural diffusions (
Finally, bash run_train
execute the experiments.
The script has been tested running under Python 3.7.9, with TensorFlow version as:
tensorflow==2.6.0
In addition, CUDA 11.4 and cuDNN 11.1 have been used.
MIT