Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural Networks

@article{Zhang2021ClassificationOP,
  title={Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural Networks},
  author={Keming Zhang and Joshua S. Bloom},
  journal={ArXiv},
  year={2021},
  volume={abs/2011.01243}
}
We present Cyclic-Permutation Invariant Neural Networks, a novel class of neural networks (NNs) designed to be invariant to phase shifts of period-folded periodic sequences by means of ‘symmetry padding’. In the context of periodic variable star light curves, initial phases are exogenous to the physical origin of the variability and should thus be immaterial to the downstream inference application. Although previous work utilizing NNs commonly operated on period-folded light curves, no… Expand

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