shadowbourne's Fork:
This is a modified fork of the original repo that instead allows forecasting of per square population density rather than 2 way flows within the grids. Used to test network's capabilities of forecasting mobile location data.
ST-ResNet in PyTorch
Demo code snippets (with dataset BikeNYC) of Deep Spatio-Temporal Residual Networks (ST-ResNet) from the paper "Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction".
Prerequisites
- Python 3.6
- Pytorch 1.0
Usage
This is only demo code snippets for reference.
Reference
Zhang, Junbo, Yu Zheng, and Dekang Qi. "Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction." AAAI. 2017. https://arxiv.org/pdf/1610.00081.pdf
Refered implementations
Keras: https://github.com/lucktroy/DeepST
Tensorflow: https://github.com/snehasinghania/STResNet