Machine-learning interpolation of population-synthesis simulations to interpret gravitational-wave observations: A case study. Wong, K. W. & Gerosa, D. Physical Review D, 100(8):083015, October, 2019. doi bibtex @article{2019PhRvD.100h3015W,
adsnote = {Provided by the SAO/NASA Astrophysics Data System},
adsurl = {https://ui.adsabs.harvard.edu/abs/2019PhRvD.100h3015W},
archiveprefix = {arXiv},
author = {{Wong}, Kaze W.~K. and {Gerosa}, Davide},
doi = {10.1103/PhysRevD.100.083015},
eid = {083015},
eprint = {1909.06373},
journal = {Physical Review D},
keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
month = oct,
number = {8},
pages = {083015},
primaryclass = {astro-ph.HE},
title = {{Machine-learning interpolation of population-synthesis simulations to interpret gravitational-wave observations: A case study}},
volume = {100},
year = 2019,
bdsk-url-1 = {https://doi.org/10.1103/PhysRevD.100.083015}}
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