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  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., 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.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-731F-A Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7320-7
Genre: Journal Article

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Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning.pdf (Abstract), 5MB
 
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 Creators:
Ishida, E. E. O., Author
Beck, R., Author
González-Gaitán, S., Author
de Souza, R. S., Author
Krone-Martins, A., Author
Barrett, J. W., Author
Kennamer, N., Author
Vilalta, R., Author
Burgess, J. M.1, Author              
Quint, B., Author
Vitorelli, A. Z., Author
Mahabal, A., Author
Gangler, E., Author
Affiliations:
1High Energy Astrophysics, MPI for Extraterrestrial Physics, Max Planck Society, ou_159890              

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 Dates: 2018-11-06
 Publication Status: Published online
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/mnras/sty3015
 Degree: -

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Title: Monthly Notices of the Royal Astronomical Society
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Source Genre: Journal
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Publ. Info: OXFORD : OXFORD UNIV PRESS
Pages: - Volume / Issue: 483 (1) Sequence Number: - Start / End Page: 2 - 18 Identifier: ISSN: 0035-8711
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000021470