AINeutralarXiv – CS AI · 8h ago6/10
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Physics-Encoded Inverse Modeling for Arctic Snow Depth Prediction
Researchers introduce Physics-Encoded Inversion (PhysE-Inv), a deep learning framework combining LSTM networks with physics-informed guidance to improve snow depth estimation in Arctic regions. The method achieves 24.7% MSE reduction over baseline models by learning latent parameters from sparse observational data, demonstrating wider applicability for inverse modeling in data-scarce scientific domains.