基于LSTM 时空序列预测任务文章部分总结

时空序列预测任务已经在交通流量，雷达回波，人体行为预测等方面有了重要作用，本博客主要针对当前所有的时空序列预测任务进行总结。下面当前收集到的所有论文的链接地址和名字，主要作为新手入行使用，避免浪费很多的时间来查找文献。下面附上论文名称和地址，以及每篇论文的中文简介。

1. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.论文下载
2. Deep Learning for Precipitation Nowcasting:A Benchmark and A New Model.论文下载
3. PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs.论文下载
4. PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning.论文下载
5. Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics.论文下载
6. PredCNN: Predictive Learning with Cascade Convolutions.论文下载
7. Deep Learning Prediction of Incoming Rainfalls:An Operational Service for the City of Beijing China.
8. Cubic LSTMs for Video Prediction.论文下载
9. Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction.论文下载
10. HPRNN: A HIERARCHICAL SEQUENCE PREDICTION MODEL FOR LONG-TERM WEATHER RADAR ECHO EXTRAPOLATION .论文下载
11. Video Pixel Networks.论文下载
12. PFST-LSTM: A SpatioTemporal LSTM Model With Pseudoflow Prediction for Precipitation Nowcasting.论文下载
13. MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions.论文下载
14. EIDETIC 3D LSTM:A MODEL FOR VIDEO PREDICTION AND BEYOND.论文下载
15. Convolutional Tensor-Train LSTM for Spatio-Temporal Learning.论文下载
16. An Energy-Based Generative Adversarial Forecaster for Radar Echo Map Extrapolation.
17. Self-Attention ConvLSTM for Spatiotemporal Prediction.论文下载

目前所搜集到的关于时空序列的文章大致只有这些，希望能帮助到初入领域的人，也为自己整理一下。