Spatiotemporal-Model

存储时序数据预测的相关模型的复现，基于tensorflow 2.0 实现 本仓库仅包含模型部分，对于数据的处理部分请参考相关论文

1. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction

模型	创新点	框架	Github
ST-ResNet			code papper

Junbo Zhang, Yu Zheng, Dekang Qi

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2. DeepSTD: Mining Spatio-Temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction

模型	创新点	框架	Github
ST-ResNet			code papper

Chuanpan Zheng , Xiaoliang Fan, Chuanpan Zheng, Xiaoliang Fan

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3. ASTIR: Spatio-Temporal Data Mining for Crowd Flow Prediction

模型	创新点	框架	Github
ASTIR			code papper

Lablack Mourad, Heng Qi , Yanming Shen, Baocai Yin

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4. DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

模型	创新点	框架	Github
DeepSTN+			code papper

Ziqian Lin, Jie Feng, Ziyang Lu, Yong Li, Depeng Jin

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5. Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

模型	创新点	框架	Github
DMVST			code papper

Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang

6. Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning

模型	创新点	框架	Github
MDL			code

Junbo Zhang, Yu Zheng, Junkai Sun, Dekang Qi

7. DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

模型	创新点	框架	Github
DeepSTN+			code

Ziqian Lin, Jie Feng, Ziyang Lu, Yong Li, Depeng Jin

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