Skip to content

The model for the paper "EEG-Based Emotion Recognition Using Regularized Graph Neural Networks"

Notifications You must be signed in to change notification settings

PieraRiccio/RGNN

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 

Repository files navigation

RGNN

This repo illustrates the RGNN model implementation in the paper EEG-Based Emotion Recognition Using Regularized Graph Neural Networks. The model is based on torch geometric v1.2.1

The EmotionDL regularizer is easy to implement and thus not included in the repo. More details can be found in the paper.

If you find the paper or this repo useful, please cite

@article{zhong2020eeg,
  title={EEG-Based Emotion Recognition Using Regularized Graph Neural Networks},
  author={Zhong, Peixiang and Wang, Di and Miao, Chunyan},
  journal={IEEE Transactions on Affective Computing},
  year={2020},
  publisher={IEEE}
}

About

The model for the paper "EEG-Based Emotion Recognition Using Regularized Graph Neural Networks"

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%