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Optimal scenario design for climate emulation

Womack, Christopher B. et al.
arXiv (All) · Papers
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As deep learning for physical systems continues to grow in popularity, efforts to improve generalizability have primarily focused on designing architectures that embed physical constraints. However, for machine-learning surrogate climate models (emulators), we show that the low structural diversity
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