Using Artificial Intelligence and Machine Learning to Enhance Mission Design and Operations of the Habitable Worlds Observatory (HWO). Poian, V. D., Moussa, M. M., Rebbapragada, U., Wu, J., Salazar-Donate, E., Shabram, M., Gharib-Nezhad, E., Toy-Edens, V., Venkataram, H., Giuliano, M., Chien, S., Moin, A., de Fourtou, G. B., Basich, C., Lyness, E., Dean, B., & Ansdell, M. In AGU Fall Meeting Abstract, Washington, DC, December, 2024. Paper bibtex 1 download @inproceedings{stv-agu2024,
address = {Washington, DC},
author = { Victoria Da Poian and Mark M. Moussa and Umaa Rebbapragada and John Wu and Emilio Salazar-Donate and Megan Shabram and Ehsan Gharib-Nezhad and Vicki Toy-Edens and Hamsa Venkataram and Mark Giuliano and Steve Chien and Aquib Moin and Gautier Bardi de Fourtou and Connor Basich and Eric Lyness and Bruce Dean and Megan Ansdell },
booktitle = {AGU Fall Meeting Abstract},
month = {December},
project = { },
title = {Using Artificial Intelligence and Machine Learning to Enhance Mission Design and Operations of the Habitable Worlds Observatory (HWO)},
year = {2024},
url = {https://ai.jpl.nasa.gov/public/documents/papers/AGU-2024-STV.pdf}
}
Downloads: 1
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