-
The Building Blocks of Interpretability https://distill.pub/2018/building-blocks/
-
Neural Networks and Deep Learning (free online book) http://neuralnetworksanddeeplearning.com/index.html
-
[NIPS 2015] Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting (Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong, Wang-chun Woo) https://arxiv.org/abs/1506.04214
-
[NIPS 2017] Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model https://arxiv.org/abs/1706.03458
-
[ICML 2017] Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting https://arxiv.org/abs/1707.08110
-
[ICML 2018] PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning https://arxiv.org/abs/1804.06300
http://proceedings.mlr.press/v80/wang18b.html
[Official CODE] https://github.com/Yunbo426/predrnn-pp -
[ICDM 2018] Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery https://arxiv.org/pdf/1804.08562.pdf
[Official CODE] https://github.com/edouardelasalles/stnn
-
Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data (Monidipa Das, Soumya K. Ghosh) https://ieeexplore.ieee.org/document/7752890
-
DeepRain: ConvLSTM Network for Precipitation Prediction Using Multichannel Radar Data (Seongchan Kim, Seungkyun Hong, Minsu Joh, Sa-kwang Song)
https://arxiv.org/abs/1711.02316 -
[CIKM 2017 Contest] Convolutional LSTM neural network to extrapolate radar images, and predict rainfal
https://github.com/TeaPearce/precipitation-prediction-convLSTM-keras -
[NIPS 2017] PSIque: Next Sequence Prediction of Satellite Images using a Convolutional Sequence-to-Sequence Network https://dl4physicalsciences.github.io/files/nips_dlps_2017_12.pdf
-
[IWCI 2017] Globenet: Convolutional neural networks for typhoon eye tracking from remote sensing imagery
-
DNN-Based Prediction Model for Spatial-Temporal Data
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/09/DeepST-SIGSPATIAL2016.pdf -
Deep Forecast: Deep Learning-based Spatio-Temporl Forecasting
http://roseyu.com/time-series-workshop/submissions/TSW2017_paper_2.pdf
- Xingjian Shi (施行健)
https://home.cse.ust.hk/~xshiab/
- Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
- NIPS Neural Information Processing Systems (NIPS)
- ICML International Conference on Machine Learning
- ICDM IEEE International Conference on Data Mining series (ICDM)
- ICWI International Workshop on Climate Informatics (ICWI)