A multi-horizon graph neural network emulator jointly predicts state increments for ice thickness and velocities at several lead times and shows higher long-range accuracy and stability than autoregressive or direct baselines on Pine Island Glacier simulations.
Journal of Glaciology69(273), 13–26 (2023)
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COGENT is a continuous graph emulator using Neural ODEs for stable long-term forecasting on irregular geospatial meshes, evaluated on ice-sheet simulations with improved stability over autoregressive baselines.
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From Short Histories to Long Futures: Horizon-Aware Graph Neural Networks for Long Horizon Forecasting
A multi-horizon graph neural network emulator jointly predicts state increments for ice thickness and velocities at several lead times and shows higher long-range accuracy and stability than autoregressive or direct baselines on Pine Island Glacier simulations.
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COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting
COGENT is a continuous graph emulator using Neural ODEs for stable long-term forecasting on irregular geospatial meshes, evaluated on ice-sheet simulations with improved stability over autoregressive baselines.