Capturing Graphs with Hypo-Elliptic Diffusions

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A novel GNN utilizing tensor features of random walks for (deep) parametric feature extraction

This code package contains supplementary code to the NeurIPS 2022 paper Capturing Graphs with Hypo-Elliptic Diffusions.

Installation

• Please create a clean conda environment, the code was tested with python==3.7.9, so ideally use the command:

  conda create -n test_env python=3.7.9
  conda activate test_env

• Install the prerequisites using pip install -r requirements.txt

Running the experiments:

• Remove/rename the results directory, since the run script skips all existing results
• Optional: Open the file configs.yaml, and remove/change the dataset/model configurations as required
• Call python run_experiments.py [GPU_ID] for running on GPU, or leave GPU_ID empty for CPU

Printing the results:

• The results for each dataset/model/seed combination are included in the results directory.
• To print a summary of results, please run python get_results.py

Further remarks:

• Compared to the paper certain naming conventions are different in the code (TODO):
  • The names of the models: GSAN == G2TAN, GSN == G2TN
  • In the variations: BP == ZeroStart, Embed == AlgOpt

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