The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves
C. Donoso-Oliva,
G. Cabrera-Vives,
P. Protopapas
et al.
Abstract:In the new era of very large telescopes, where data is crucial to expand scientific knowledge, we have witnessed many deep learning applications for the automatic classification of lightcurves. Recurrent neural networks (RNNs) are one of the models used for these applications, and the LSTM unit stands out for being an excellent choice for the representation of long time series. In general, RNNs assume observations at discrete times, which may not suit the irregular sampling of lightcurves. A traditional techni… Show more
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