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Probabilistic Machine Learning for Short-Term Atmospheric Seeing Forecasting
Accurate short-term forecasting of atmospheric seeing is of significant interest for astronomical observations and free-space optical communication systems, where rapid variations in optical turbulence can affect system performance and operational planning. In this work, we benchmark machine learnin
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