/IrregularTimeSeriesAutoencoderPaper

Primary LanguageJupyter NotebookMIT LicenseMIT

Neural network autoencoders for unevenly sampled time series

DOI

Code accompanying "A recurrent neural network for classification of unevenly sampled variable stars".

  • Code for scores/figures is found in figures.ipynb
  • Autoencoder network architecture is defined in autoencoder.py
  • Experiments for simulated data are found in autoencoder.main
  • Experiments for light curve data are found in survey_autoencoder.main
    • Light curve data is in ./data
  • Model weights are saved in ./keras_logs