GND-Nets (Graph Neural Diffusion Networks) in TensorFlow.

Overview

GNDC

For submission to IEEE TKDE.

Overview

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, and gndnets_ds.py);
  • utils/ contains:
    • an implementation of three variants of graph neural diffusions (layers.py);
    • preprocessing subroutines (process.py);

Finally, bash run_train execute the experiments.

Dependencies

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.

License

MIT

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