Graph Neural Controlled Differential Equations for Traffic Forecasting

Introduction

This is the repository of our accepted AAAI 2022 paper "Graph Neural Controlled Differential Equations for Traffic Forecasting". Paper is available on arxiv.

Citation

If you find this code useful, you may cite us as:

@inproceedings{choi2022STGNCDE,
  title={Graph Neural Controlled Differential Equations for Traffic Forecasting},
  author={Jeongwhan Choi AND Hwangyong Choi AND Jeehyun Hwang AND Noseong Park},
  booktitle={AAAI},
  year={2022}
}

Setup Python environment for STG-NCDE

Install python environment

$ conda env create -f environment.yml

Reproducibility

Usage

In terminal

Run the shell file (at the root of the project)

$ bash run.sh

Run the python file (at the model folder)

$ cd model

$ python Run_cde.py --dataset='PEMSD4' --model='GCDE' --model_type='type1' --embed_dim=10 --hid_dim=64 --hid_hid_dim=64 --num_layers=2 --lr_init=0.001 --weight_decay=1e-3 --epochs=200 --tensorboard --comment="" --device=0