Participants of the Berlin Summit on Earth Virtualization Engines (EVEs)...
Modern climate projections lack adequate spatial and temporal resolution...
Fourier Neural Operators (FNOs) have proven to be an efficient and effec...
Nonlinearly interacting system components often introduce instabilities ...
Data-driven models, such as FourCastNet (FCN), have shown exemplary
perf...
Extreme weather amplified by climate change is causing increasingly
deva...
FourCastNet, short for Fourier Forecasting Neural Network, is a global
d...
There is growing interest in data-driven weather prediction (DDWP), for
...
Simulation of turbulent flows at high Reynolds number is a computational...
We propose MeshfreeFlowNet, a novel deep learning-based super-resolution...
While deep learning has shown tremendous success in a wide range of doma...
Extracting actionable insight from complex unlabeled scientific data is ...
Extreme weather is one of the main mechanisms through which climate chan...
Simulating complex physical systems often involves solving partial
diffe...
We present an efficient convolution kernel for Convolutional Neural Netw...