Optimizing spectroscopic follow-up strategies for supernova photometric 
classification with active learning

Ishida, E. E. O.; Beck, R.; González-Gaitán, S.; de Souza, R. S.; Krone-Martins, A.; Barrett, J. W.; Kennamer, N.; Vilalta, R.; Burgess, J. M.; Quint, B.; Vitorelli, A. Z.; Mahabal, A.; Gangler, E.

doi:10.1093/mnras/sty3015

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Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning

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Burgess, J. M.
High Energy Astrophysics, MPI for Extraterrestrial Physics, Max Planck Society;

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Ishida, E. E. O., Beck, R., González-Gaitán, S., de Souza, R. S., Krone-Martins, A., Barrett, J. W., et al. (2018). Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning. Monthly Notices of the Royal Astronomical Society, 483(1), 2-18. doi:10.1093/mnras/sty3015.

Cite as: https://hdl.handle.net/21.11116/0000-0003-731F-A

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