SFNO surrogate matches or exceeds HUX on several solar-wind metrics while remaining trainable on additional data.
Solar wind prediction using deep learning,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2025 2verdicts
UNVERDICTED 2representative citing papers
Long-term near-Earth solar wind observations establish a robust empirical connection between flow speed and magnetohydrodynamic turbulence energy.
citing papers explorer
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Toward Data-Driven Surrogates of the Solar Wind with Spherical Fourier Neural Operator
SFNO surrogate matches or exceeds HUX on several solar-wind metrics while remaining trainable on additional data.
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A robust empirical relationship between speed and turbulence energy in the near-Earth solar wind
Long-term near-Earth solar wind observations establish a robust empirical connection between flow speed and magnetohydrodynamic turbulence energy.