Spatio-Temporal Graph Convolutional Networks
The PyTorch version of STGCN implemented by the paper Spatio-Temporal Graph Convolutional Networks:
A Deep Learning Framework for Traffic Forecasting with tons of bugs fixed.
https://arxiv.org/abs/1709.04875
TCN: An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
GLU and GTU: Language Modeling with Gated Convolutional Networks
ChebyNet: Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
GCN: Semi-Supervised Classification with Graph Convolutional Networks
TCN: https://github.com/locuslab/TCN
ChebyNet: https://github.com/mdeff/cnn_graph
GCN: https://github.com/tkipf/pygcn
METR-LA: DCRNN author's Google Drive
PEMS-BAY: DCRNN author's Google Drive
PeMSD7(M): STGCN author's GitHub repository
Using the formula from ChebyNet :
Differents of code between mine and author's
Fix tons of bugs
Add Early Stopping approach
Add Dropout approach
Offer a different set of hyperparameters
Offer config files for two different categories graph convolution
Add datasets METR-LA and PEMS-BAY
Using a different data preprocessing method
To install requirements:
pip3 install -r requirements.txt
METR-LA (15/30/60 mins) (train: val: test = 70: 15: 15)
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
3.825249
7.949693
7.530186%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
3.703660
7.685864
7.290832%
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
4.789775
9.501917
9.430166%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
4.518740
8.863177
8.896550%
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
6.047641
11.888628
11.909882%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
5.997484
11.498759
11.811108%
PEMS-BAY (15/30/60 mins) (train: val: test = 70: 15: 15)
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
1.504175
3.031081
2.420486%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
1.472308
2.987471
2.369206%
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
1.919455
3.964940
3.088833%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
1.910708
3.948517
3.074757%
Model (paper)
Model (code)
Laplacian matrix type
Gated activation function
MAE
RMSE
WMAPE
STGCN (Cheb)
STGCN_ChebConv (Ks=3, Kt=3)
sym
GLU
2.308847
4.690512
3.715672%
STGCN (1st )
STGCN_GCNConv (Kt=3)
sym
GLU
2.306092
4.701984
3.711238%