This AI Paper Unveils Mixed-Precision Training for Fourier Neural Operators: Bridging Efficiency and Precision in High-Resolution PDE Solutions

Neural operators, specifically the Fourier Neural Operators (FNO), have revolutionized how researchers approach solving partial differential equations (PDEs), a cornerstone problem in science and engineering. These operators have shown exceptional promise in learning mappings between function spaces, pivotal for accurately simulating phenomena like climate modeling and fluid dynamics. Despite their potential, the substantial computational resources […]

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