PACT introduces a peak-aware cross-attention graph transformer that emulates station-level storm surges more accurately than prior graph neural network baselines while running in seconds after training.
Graph convolutional network as a fast statistical emulator for numerical ice sheet modeling , volume=
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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.
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.
citing papers explorer
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PACT: Peak-Aware Cross-Attention Graph Transformers for Efficient Storm-Surge Emulation
PACT introduces a peak-aware cross-attention graph transformer that emulates station-level storm surges more accurately than prior graph neural network baselines while running in seconds after training.
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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.