Mutual Information Based Reweighting for Precipitation Nowcasting

[1]  Raia Hadsell,et al.  Skilful precipitation nowcasting using deep generative models of radar , 2021, Nature.

[2]  Philip S. Yu,et al.  PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Hao Wang,et al.  Delving into Deep Imbalanced Regression , 2021, ICML.

[4]  Cesare Furlanello,et al.  TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting , 2020, Scientific Data.

[5]  Zhi Xu,et al.  Rethinking the Value of Labels for Improving Class-Imbalanced Learning , 2020, NeurIPS.

[6]  Tobias Scheffer,et al.  RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting , 2020, Geoscientific Model Development.

[7]  Philip S. Yu,et al.  PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs , 2017, NIPS.

[8]  Dit-Yan Yeung,et al.  Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model , 2017, NIPS.

[9]  Dit-Yan Yeung,et al.  Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.

[10]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[11]  Nitesh V. Chawla,et al.  Editorial: special issue on learning from imbalanced data sets , 2004, SKDD.

[12]  Dennis DeCoste,et al.  Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum , 2019, NeurIPS.