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  Exploring the spectroscopic diversity of Type Ia supernovae with dracula: a machine learning approach

Sasdelli, M., Ishida, E. E. O., Vilalta, R., Aguena, M., Busti, V. C., Camacho, H., et al. (2016). Exploring the spectroscopic diversity of Type Ia supernovae with dracula: a machine learning approach. Monthly Notices of the Royal Astronomical Society, 461(2), 2044-2059. doi:10.1093/mnras/stw1228.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-9973-8 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-9974-6
Genre: Journal Article

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 Creators:
Sasdelli, M.1, Author              
Ishida, E. E. O.1, Author              
Vilalta, R., Author
Aguena, M., Author
Busti, V. C., Author
Camacho, H., Author
Trindade, A. M. M., Author
Gieseke, F., Author
de Souza, R. S., Author
Fantaye, Y. T., Author
Mazzali, P. A.1, Author              
Affiliations:
1Stellar Astrophysics, MPI for Astrophysics, Max Planck Society, ou_159882              

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Language(s): eng - English
 Dates: 2016-09-11
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1093/mnras/stw1228
 Degree: -

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Title: Monthly Notices of the Royal Astronomical Society
  Abbreviation : Mon. Not. Roy. Astron. Soc.
Source Genre: Journal
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Pages: - Volume / Issue: 461 (2) Sequence Number: - Start / End Page: 2044 - 2059 Identifier: ISSN: 0035-8711
ISSN: 1365-8711