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New Deep Learning Data Analysis Method for PROSPECT using GAPE: Genetic Algorithm Powered Evolution

Fuente: arXiv

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Bibliographic Details
Main Authors:	Adriamirado, M., Balantekin, A. B., Bass, C., Rodrigues, O. Benevides, Bernard, E. P., Bowden, N. S., Bryan, C. D., Classen, T., Conant, A. J., Craft, N., Delgado, A., Deichert, G., Dolinski, M. J., Erickson, A., Fuller, M., Galindo-Uribarri, A., Ghosh, S., Gokhale, S., Grant, C., Hans, S., Hansell, A. B., Haugen, T. E., Heeger, K. M., Heffron, B., Irani, A., Koblanski, J., Lane, C. E., Littlejohn, B. R., Sanchez, A. Lozano, Maricic, J., Machado, F., Mendenhall, M. P., Meyer, A. M., Milincic, R., Mueller, P. E., Mumm, H. P., Neilson, R., Roca, C., Rosero, R., Venegas-Vargas, D., Wilhelmi, J., Yeh, M., Zhang, X.
Format:	Preprint
Published:	2026
Subjects:	Data Analysis, Statistics and Probability High Energy Physics - Experiment
Online Access:	Acceder al recurso
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