26 citations · 26 across the 2 of their papers we have counts for
4 papers
Physics-informed generative neural network: an application to troposphere temperature prediction
Zhihao Chen, Jie Gao, Weikai Wang +1
The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle…
Channel-wise Knowledge Distillation for Dense Prediction
Changyong Shu, Yifan Liu, Jianfei Gao +2
Knowledge distillation (KD) has been proven to be a simple and effective tool for training compact models. Almost all KD variants for dense prediction tasks align the student and t…
Deep Variational Luenberger-type Observer for Stochastic Video Prediction
Dong Wang, Feng Zhou, Zheng Yan +4
Considering the inherent stochasticity and uncertainty, predicting future video frames is exceptionally challenging. In this work, we study the problem of video prediction by combi…
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
Bin Wang, Jie Lu, Zheng Yan +4
Weather forecasting is usually solved through numerical weather prediction (NWP), which can sometimes lead to unsatisfactory performance due to inappropriate setting of the initial…