Direct sampling under a uniform-in-dL prior raises P(H0>120) from 0.017 to 0.159 for GW170817; post-hoc reweighting recovers only 0.041 because a low-dL mode is undersampled.
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Score-based diffusion models learn the empirical distribution of real LIGO noise to enable unbiased gravitational-wave parameter estimation under only an additivity assumption.
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Rapid Hubble constant inference from GW170817 using GPU-accelerated nested sampling: prior sensitivity and the limits of post-hoc reweighting
Direct sampling under a uniform-in-dL prior raises P(H0>120) from 0.017 to 0.159 for GW170817; post-hoc reweighting recovers only 0.041 because a low-dL mode is undersampled.
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Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization
Score-based diffusion models learn the empirical distribution of real LIGO noise to enable unbiased gravitational-wave parameter estimation under only an additivity assumption.