Skip to content
/ EFT Public

The code for our ICLR 2024 paper: "Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs"

Notifications You must be signed in to change notification settings

ansonb/EFT

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 

Repository files navigation

Evolving Graph Fourier Transform (EFT)

The code for our ICLR 2024 paper: "Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs" (https://openreview.net/forum?id=uvFhCUPjtI). We have implemented our methods in Pytorch.

Dependencies

  • Python 3.7
  • torch 1.11.0
  • dgl 0.8.2

Usage

Generate data

You need to run the file new_data.py to generate the data format needed for the model. The detailed commands can be found in load_{dataset}.sh

You need to run the file generate_neg.py to generate data to speed up the test. You can set the data set in the file.

Training and Testing

Then you can run the file new_main.py to train and test our model on the SR datasets. The detailed commands can be found in load_{dataset}.sh

Cite

If our research has benefited you, please cite:

@inproceedings{
bastos2024beyond,
title={Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs},
author={Anson Bastos and Kuldeep Singh and Abhishek Nadgeri and Manish Singh and Toyotaro Suzumura},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=uvFhCUPjtI}
}

About

The code for our ICLR 2024 paper: "Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs"

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published