This is a rough reproduction of the paper EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks, including the dynamical graph convolutional layer only.
The code is adapted from this open access repository.
To run the code, you can use commands below:
# GCN
python main.py --model_name GCN --max_epochs 3000 --learning_rate 0.001 --weight_decay 0 --batch_size 64 --hidden_dim 100 --settings supervised --gpus 1
# DGCNN
python main.py --model_name DGCNN --max_epochs 3000 --learning_rate 0.001 --weight_decay 0 --batch_size 64 --hidden_dim 100 --settings supervised --gpus 1
The value of parameters like max_epochs, learning_rate can be adjusted.
Run tensorboard --logdir lightning_logs/version_0 to monitor the training progress and view the prediction results.