A depth-aware conditional diffusion model reconstructs high-resolution 3D ocean states from extremely sparse surface observations in the Gulf of Mexico.
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A framework builds stable neural models of turbulent dynamics by enforcing energy-preserving nonlinearities and causal constraints in discrete-time flow maps, demonstrated on Charney-DeVore and Lorenz-96 systems.
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High-resolution probabilistic estimation of three-dimensional regional ocean dynamics from sparse surface observations
A depth-aware conditional diffusion model reconstructs high-resolution 3D ocean states from extremely sparse surface observations in the Gulf of Mexico.
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Physics and causally constrained discrete-time neural models of turbulent dynamical systems
A framework builds stable neural models of turbulent dynamics by enforcing energy-preserving nonlinearities and causal constraints in discrete-time flow maps, demonstrated on Charney-DeVore and Lorenz-96 systems.