文件列表:

LICENSE (1069, 2018-12-12)
data (0, 2018-12-12)
data\METR-LA.zip (15719519, 2018-12-12)
main.py (4936, 2018-12-12)
stgcn.py (5131, 2018-12-12)
utils.py (2378, 2018-12-12)

# STGCN-PyTorch PyTorch implementation of the spatio-temporal graph convolutional network proposed in [Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting](https://arxiv.org/abs/1709.04875) by Bing Yu, Haoteng Yin, Zhanxing Zhu. An example for traffic forecasting is included in this repository. Alternative implementations using other deep learning frameworks can be found here: * [TensorFlow](https://github.com/PKUAI26/STGCN-IJCAI-18) by [PKUAI26](https://github.com/PKUAI26) * [MXNet](https://github.com/Davidham3/STGCN) by [Davidham3](https://github.com/Davidham3) ## Requirements * PyTorch * NumPy * Matplotlib ## Example Dataset The repository provides a usage example on the METR-LA dataset (original version to be found [here](https://github.com/liyaguang/DCRNN)). Unfortunately, there is no publicly available standard version of the PeMSD dataset used in the paper.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：