A Deep-learning Approach for Live Anomaly Detection of Extragalactic Transients

@article{Villar2021ADA,
  title={A Deep-learning Approach for Live Anomaly Detection of Extragalactic Transients},
  author={V. Ashley Villar and M. Cranmer and Edo Berger and Gabriella Contardo and Shirley Ho and Griffin Hosseinzadeh and Joshua Yao-Yu Lin},
  journal={The Astrophysical Journal Supplement Series},
  year={2021},
  volume={255}
}
There is a shortage of multiwavelength and spectroscopic follow-up capabilities given the number of transient and variable astrophysical events discovered through wide-field optical surveys such as the upcoming Vera C. Rubin Observatory and its associated Legacy Survey of Space and Time. From the haystack of potential science targets, astronomers must allocate scarce resources to study a selection of needles in real time. Here we present a variational recurrent autoencoder neural network to… 

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