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We apply neural posterior estimation for fast-and-accurate hierarchical Bayesian inference of gravitational wave populations.
1903
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T. Akutsu et al. (KAGRA), Overview of KAGRA: Detector design and construction history, PTEP 2021
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E. G. Tabak and E. Vanden-Eijnden, Density estimation by dual ascent of the log-likelihood, Communications in Mathematical Sciences 8
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E. G. Tabak and C. V. Turner, A family of nonparametric density estimation algorithms, Communications on Pure and Applied Mathematics 66
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J. Aasi et al. , Advanced LIGO, Classical and Quantum Gravity 32
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2015
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2018
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M. Tse et al. , Quantum-Enhanced Advanced LIGO Detectors in the Era of Gravitational-Wave Astronomy, Phys. Rev. Lett. 123
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F. Acernese et al. (Virgo), Increasing the Astrophysical Reach of the Advanced Virgo Detector via the Application of Squeezed Vacuum States of Light, Phys. Rev. Lett. 123
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F. Noé, S. Olsson, J. Köhler, and H. Wu, Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning, Science 365
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2022
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I. Gupta, Using Gray Sirens to Resolve the Hubble-Lemaître Tension, (2022), arXiv:2212.00163 [gr-qc]
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