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Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction
This is a Pytorch implementation of SHARE architecture as described in the paper Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction.
<p align="center"> <img width="600" height="380.5" src=./figs/framework.png> </p>If you take advantage of the SHARE model in your research, please cite the following:
@inproceedings{zhang2019semi,
title={Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction},
author={Zhang, Weijia and Liu, Hao and Liu, Yanchi and Zhou, Jingbo and Xiong, Hui},
booktitle={Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence},
pages={1186--1193},
year={2020}
}
Requirements
This code is based on Python3 (>= 3.6). There are a few dependencies to run the code. The major libraries are listed as follows:
- Pytorch (0.4.1)
- dgl (0.4.1)