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Abstract: <i>Connecting the Dots: A Machine Learning Ready Foundational Dataset for Ionospheric Forecasting Models</i> (AGU25)

Connecting the Dots: A Machine Learning Ready Foundational Dataset for Ionospheric Forecasting Models

Michael Vergalla1, Simone Mestici2, Linnea Wolniewicz3, Halil S. Kelebek4, Giacomo Acciarini5, Bala Poduval6, Umaa Rebbapragada7, Olga P Verkhoglyadova8, Atılım Güneş Baydin4, Tom Berger9 and Frank Soboczenski10, (1)FREE FLIGHT RESEARCH LAB, Mountain View, United States, (2)Sapienza University of Rome, Rome, Italy, (3)University of Hawaii at Manoa, Information and Computer Sciences, Honolulu, United States, (4)University of Oxford, Department of Engineering Science, Oxford, United Kingdom, (5)ESA & University of Surrey, Advanced Concepts Team, Noordwijk, Netherlands, (6)Space Science Institute, Boulder, CO, United States, (7)Jet Propulsion Laboratory, California Institute of Technology, Machine Learning and Instrument Autonomy, Pasadena, United States, (8)NASA Jet Propulsion Laboratory, Pasadena, United States, (9)University of Colorado at Boulder, CIRES, Boulder, United States, (10)University of York & King's College, Department of Computer Science, London, United Kingdom
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