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Deep learning in turbulent convection networks
We explore heat transport properties of turbulent Rayleigh–Bénard convection in horizontally extended systems by using deep-learning algorithms that greatly reduce the number of degrees of freedom. Particular attention is paid to the slowly evolving turbulent superstructures—so called because they a...
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| Veröffentlicht in: | Proc Natl Acad Sci U S A |
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| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
National Academy of Sciences
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6500159/ https://ncbi.nlm.nih.gov/pubmed/30988195 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1900358116 |
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