Ice-flow model emulator based on physics-informed deep learning
Convolutional neural networks (CNN) trained from high-order ice-flow model realisations have proven to be outstanding emulators in terms of fidelity and computational performance. However, the dependence on an ensemble of realisations of an instructor model renders this strategy difficult to general...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2023-12-01
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| Series: | Journal of Glaciology |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143023000734/type/journal_article |
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