Transient-optimized real-bogus classification with Bayesian convolutional neural networks - sifting the GOTO candidate stream
Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional
Killestein, T. L. et al.
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5
2021