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.
IET Microwaves, Antennas & Propagation18(7), 505–515 (2024)
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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.