On neural architectures for astronomical time-series classification

@inproceedings{Jamal2020OnNA,
  title={On neural architectures for astronomical time-series classification},
  author={S. Jamal and J. Bloom},
  year={2020}
}
Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse datasets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time-series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical… Expand

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