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Inpainting Computational Fluid Dynamics with Deep Learning
Fluid data completion is a research problem with high potential benefit for both experimental and computational fluid dynamics.
Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
Neural networks have shown promising potential in accelerating the numerical simulation of systems governed by partial differential equations (PDEs).
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