Research Papers Explaining Some of the Pipelines

Hello folks!
For those of you who want to go deeper and understand the theory/implementation of certain terminologies that you may encounter while exploring various aspects of GW data analysis, here are a few useful research papers that explain the respective pipelines in detail.

BAYESTAR: Singer et. al. (2016); ArXiv: https://doi.org/10.48550/arXiv.1508.03634; Publisher: Phys. Rev. D 93, 024013 (2016) - Rapid Bayesian position reconstruction for gravitational-wave transients
BayesWave: Cornish et. al. (2015); ArXiv: https://doi.org/10.48550/arXiv.1410.3835; Publisher: ShieldSquare Captcha
BayesWave updates: Cornish et. al. (2021); ArXiv: https://doi.org/10.48550/arXiv.2011.09494; Publisher: Phys. Rev. D 103, 044006 (2021) - BayesWave analysis pipeline in the era of gravitational wave observations
Bilby: Ashton et. al. (2019); ArXiv: https://doi.org/10.48550/arXiv.1811.02042; Publisher: ShieldSquare Captcha
GWpy: Macleod et. al. (2021); Publisher: Redirecting
PyCBC: Usman et. al. (2016); ArXiv: https://doi.org/10.48550/arXiv.1508.02357; Publisher: ShieldSquare Captcha

This list is by no means an exhaustive one. You are always welcome to contribute to this thread.
Happy learning!

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