Modern climate projections lack adequate spatial and temporal resolution...
Fourier Neural Operators (FNOs) have proven to be an efficient and effec...
Data-driven models, such as FourCastNet (FCN), have shown exemplary
perf...
Extreme weather amplified by climate change is causing increasingly
deva...
Recent years have seen a surge in interest in building deep learning-bas...
FourCastNet, short for Fourier Forecasting Neural Network, is a global
d...
We consider the problem of data-assisted forecasting of chaotic dynamica...
Simulation of turbulent flows at high Reynolds number is a computational...
We consider the commonly encountered situation (e.g., in weather forecas...
We introduce and test a general machine-learning-based technique for the...
How effective are Recurrent Neural Networks (RNNs) in forecasting the
sp...
A model-based approach to forecasting chaotic dynamical systems utilizes...