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Found 6 papers, 2 papers with code
ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution
In this paper, we show that the 3D local processing in Pangu-Weather is computationally sub-optimal.
AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning
Here, we propose AtmoRep, a novel, task-independent stochastic computer model of atmospheric dynamics that can provide skillful results for a wide range of applications.
A Multi-Scale Deep Learning Framework for Projecting Weather Extremes
Weather extremes are a major societal and economic hazard, claiming thousands of lives and causing billions of dollars in damage every year.
AtmoDist: Self-supervised Representation Learning for Atmospheric Dynamics
Representation learning has proven to be a powerful methodology in a wide variety of machine learning applications.
Towards Representation Learning for Atmospheric Dynamics
The prediction of future climate scenarios under anthropogenic forcing is critical to understand climate change and to assess the impact of potentially counter-acting technologies.
Local Fourier Slice Photography
Image reconstruction then amounts to applying these filters to the light field's wavelet coefficients, and hence no reconstruction of a dense pixel representation is required.
