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Interpretable Patch-Based Deep Learning for Wildfire Spread Prediction from Ensemble Simulations
Wildfire spread is traditionally predicted using physics-based simulators, which are physically interpretable but whose cost increases with each additional ensemble member. We ask how well deep learning surrogates can reproduce these simulations at a fraction of this cost, training them on 10,584 fi
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