Deep recurrent neural networks for supernovae classification
(2017)
Journal Article
Charnock, T., & Moss, A. (2017). Deep recurrent neural networks for supernovae classification. Astrophysical Journal, 837(2), https://doi.org/10.3847/2041-8213/aa603d
We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae (code available at https://github.com/adammoss/supernovae). The observational time and filter fluxes are used as inputs to t... Read More about Deep recurrent neural networks for supernovae classification.