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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Summary of open source code for deep learning models in the field of traffic prediction
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# Deep learning models for traffic prediction This is a summary for deep learning models with open code for traffic prediction. These models are classified based on the following tasks. - Traffic flow prediction - Traffic speed prediction - On-Demand service prediction - Travel time prediction - Traffic accident prediction - Traffic location prediction - Others | Task | Model | Paper | Code | Publication | | :--------------------------: | :-------------------: | :----------------------------------------------------------: | ----------------------- | ------------------------------------------------------------ | | Traffic flow prediction | ST-ResNet | [Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction](https://arxiv.org/abs/1610.00081) | [tf](https://github.com/snehasinghania/STResNet)，[Pytorch](https://github.com/BruceBinBoxing/ST-ResNet-Pytorch)，[Keras](https://github.com/Snow-Dancing/DeepST-ResNet) | AAAI2017/A | | | ACFM | [ACFM: A Dynamic Spatial-Temporal Network for Traffic Prediction](https://dl.acm.org/doi/10.1145/3240508.3240681) | [Pytorch](https://github.com/liulingbo918/ATFM) | ACM MM2018/A | | | STDN | [Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction](https://www.aaai.org/ojs/index.php/AAAI/article/view/4511) | [Keras](https://github.com/tangxianfeng/STDN) | AAAI2019/A | | | ASTGCN | [Attention based spatial-temporal graph convolutional networks for traffic flow forecasting](https://www.aaai.org/ojs/index.php/AAAI/article/view/3881) | [Pytorch](https://github.com/guoshnBJTU/ASTGCN-r-Pytorch) | AAAI2019/A | | | ST-MetaNet | [Urban traffic prediction from spatio-temporal data using deep meta learning](https://dl.acm.org/doi/abs/10.1145/3292500.3330884) | [MXNet](https://github.com/panzheyi/ST-MetaNet) | KDD2019/A | | | STSGCN | [Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting](https://www.aaai.org/ojs/index.php/AAAI/article/view/5438) | [MXNet](https://github.com/Davidham3/STSGCN) | AAAI2020/A | | | STGNN | [STGNN: Traffic Flow Prediction via Spatial Temporal Graph Neural Network](https://dl.acm.org/doi/abs/10.1145/3366423.3380186) | [Pytorch](https://github.com/LMissher/STGNN) | WWW2020/A | | | AGCRN | [Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting](https://arxiv.org/abs/2007.02842) | [Pytorch](https://github.com/LeiBAI/AGCRN) | NIPS2020/A | | | DSAN | [Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction](https://dl.acm.org/doi/10.1145/3394486.3403046) | [tf2](https://github.com/hxstarklin/DSAN) | KDD2020/A | || MPGCN | [Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network](https://ieeexplore.ieee.org/abstract/document/9101359) | [Pytorch](https://github.com/underdoc-wang/MPGCN) | ICDE2020/A | | | ST-GDN | [Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network](https://www.aaai.org/AAAI21Papers/AISI-9334.ZhangX.pdf) | [tf](https://github.com/jillbetty001/ST-GDN) | AAAI2021/A | | | TrGNN | [Traffic Flow Prediction with Vehicle Trajectories](https://wands.sg/publications/full_list/papers/AAAI_21_1.pdf) | [Pytorch](https://github.com/mingqian000/TrGNN) | AAAI2021/A |
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