455 citations · 711 across the 25 of their papers we have counts for
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Generative Modeling of High-resolution Global Precipitation Forecasts
James Duncan, Shashank Subramanian, Peter Harrington
Forecasting global precipitation patterns and, in particular, extreme precipitation events is of critical importance to preparing for and adapting to climate change. Making accurat…
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators
Thorsten Kurth, Shashank Subramanian, Peter Harrington +6
Extreme weather amplified by climate change is causing increasingly devastating impacts across the globe. The current use of physics-based numerical weather prediction (NWP) limits…
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney +1
Physics-informed neural networks (PINNs) incorporate physical knowledge from the problem domain as a soft constraint on the loss function, but recent work has shown that this can l…
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Jaideep Pathak, Shashank Subramanian, Peter Harrington +10
FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.2…