NeurIPS 2021 paper 'Representation Learning on Spatial Networks' code

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Deep Learning SGMP_code
Overview

Representation Learning on Spatial Networks

This repository is the official implementation of Representation Learning on Spatial Networks.

Training

Examples of running the models:

**1. training the SGMP model on BACE dataset:

  • bash run_SGMP_BACE.sh

**2. training the SGMP model with sampling spanning trees on BACE dataset:

  • bash run_SGMP_st_BACE.sh

**3. training the PointNet benchmark model on BACE dataset:

  • bash run_PointNet_BACE.sh

**4. training the SGMP model on QM9 dataset for target 0 ($\mu$):

  • bash run_SGMP_QM9.sh

**5. training the SGMP model with sampling spanning trees on QM9 dataset for target 0 ($\mu$):

  • bash run_SGMP_st_QM9.sh

**6. training the PointNet benchmark model on QM9 dataset for target 0 ($\mu$):

  • bash run_PointNet_QM9.sh

**7. generate synthetic dataset

  • cd data
  • python build_synthetic_data.py

Evaluation

The evaluation will be given in the ./results

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Comments
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    Brain dataset

    Hello, I was trying to run the brain dataset but I couldn't find the data. The locations are defined in brain_load_data.py but, there is no data available. Where can I get the dataset?

    Thanks,

    opened by fmocking 0
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