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  • [2310. 00813] OceanNet: A principled neural operator-based digital twin . . .
    This study introduces OceanNet, a principled neural operator-based digital twin for ocean circulation OceanNet uses a Fourier neural operator and predictor-evaluate-corrector integration scheme to mitigate autoregressive error growth and enhance stability over extended time scales
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  • OceanNet: A principled neural operator-based digital twin for regional . . .
    This study introduces OceanNet, a principled neural operator-based digital twin for regional sea-suface height emulation OceanNet uses a Fourier neural operator and predictor-evaluate-corrector integration scheme to mitigate autoregressive error growth and enhance stability over extended time scales
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    udy introduces OceanNet, a principled neural operator-based digital twin for regional sea-suface height emula-tion OceanNet uses a Fourier neural operator and predictor-evaluate-c rrector integration scheme to mitigate autoregressive error growth a
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    In this paper, we propose a novel low-cost large-scale maritime communication architecture called OceanNet by taking advantage of D2D communication technology We have performed extensive
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    ean modeling poses distinct challenges due to complex bathymetry, land, vertical structure, and flow no -linearity This study introduces OceanNet, a principled neu-ral operator-based digital twin for ocean circulation OceanNet uses a Fourier neural operator and predictor-evaluate-c
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    OceanNet, on average, outperforms SSH predictions made by the state-of-the-art Regional Ocean Modeling System (ROMS) across a 120-day period while maintaining a computational cost that is 4,000,000x cheaper (ROMS:10 hours across 144 CPUs; OceanNet: 1 18 seconds on a single NVIDIA A100 GPU)
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    This study introduces OceanNet, a principled neural operator-based digital twin for regional sea-suface height emulation OceanNet uses a Fourier neural operator and predictor-evaluate-corrector integration scheme to mitigate autoregressive error growth and enhance stability over extended time scales
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    OceanNet uses a Fourier neural operator and predictor-evaluate-corrector integration scheme to mitigate autoregressive error growth and enhance stability over extended time scales A spectral regularizer counteracts spectral bias at smaller scales
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