Paper Citation Record · LEDGER

Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2304.06138.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2304.06138 v2

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Pith citing papers itemized under the disclosed page cap.

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Pith citing papers

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Constraining Population III stellar demographics with next-generation gravitational-wave observatories cites this paper.

Constraining Population III stellar demographics with next-generation gravitational-wave observatories Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 159

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The Long Road to Alignment: Measuring Black Hole Spin Orientation with Expanding Gravitational-Wave Datasets cites this paper.

The Long Road to Alignment: Measuring Black Hole Spin Orientation with Expanding Gravitational-Wave Datasets Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 93

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Comparing astrophysical models to gravitational-wave data in the observable space cites this paper.

Comparing astrophysical models to gravitational-wave data in the observable space Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 63

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Disentangling spinning and nonspinning binary black hole populations with spin sorting cites this paper.

Disentangling spinning and nonspinning binary black hole populations with spin sorting Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 77

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When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference cites this paper.

When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 64

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Evidence for Three Subpopulations of Merging Binary Black Holes at Different Primary Masses cites this paper.

Evidence for Three Subpopulations of Merging Binary Black Holes at Different Primary Masses Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 113

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Measurement prospects for the pair-instability mass cutoff with gravitational waves cites this paper.

Measurement prospects for the pair-instability mass cutoff with gravitational waves Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 109

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A unified harmonic framework for dark siren cosmology cites this paper.

A unified harmonic framework for dark siren cosmology Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 111

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Emergent structure in the binary black hole mass distribution and implications for population-based cosmology cites this paper.

Emergent structure in the binary black hole mass distribution and implications for population-based cosmology Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 116

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Gravitational-wave astronomy requires population-informed parameter estimation cites this paper.

Gravitational-wave astronomy requires population-informed parameter estimation Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 40

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Gravitational-wave astronomy requires population-informed parameter estimation cites this paper.

Reference 40

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How do the LIGO-Virgo-KAGRA's Heavy Black Holes Form? No evidence for core-collapse Intermediate-mass black holes in GWTC-4 cites this paper.

How do the LIGO-Virgo-KAGRA's Heavy Black Holes Form? No evidence for core-collapse Intermediate-mass black holes in GWTC-4 Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 182

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End-to-End Population Inference from Gravitational-Wave Strain using Transformers cites this paper.

End-to-End Population Inference from Gravitational-Wave Strain using Transformers Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 11

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Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run cites this paper.

Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 93

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Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run cites this paper.

Reference 93

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Gravitational-wave constraints on $H_0$ are robust to (putative) redshift evolution in the binary black hole mass spectrum at current sensitivity cites this paper.

Gravitational-wave constraints on $H_0$ are robust to (putative) redshift evolution in the binary black hole mass spectrum at current sensitivity Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 43

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Scalable Dark Siren Cosmology with gwcosmo: GPU Acceleration, Validation and Systematics cites this paper.

Scalable Dark Siren Cosmology with gwcosmo: GPU Acceleration, Validation and Systematics Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 38

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Constraining Gravitational Wave Memory with Hierarchical Inference cites this paper.

Constraining Gravitational Wave Memory with Hierarchical Inference Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 144

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The first decade of gravitational-wave measurements of black hole spins cites this paper.

The first decade of gravitational-wave measurements of black hole spins Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 266

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Evidence for additional structure in the effective spin distribution hints at multiple formation pathways in GWTC-5.0 cites this paper.

Evidence for additional structure in the effective spin distribution hints at multiple formation pathways in GWTC-5.0 Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 124

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Fortifying gravitational-wave population inference with normalizing flows cites this paper.

Fortifying gravitational-wave population inference with normalizing flows Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 24

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First analytical coverage bounds of a fully specified nested sampling algorithm cites this paper.

First analytical coverage bounds of a fully specified nested sampling algorithm Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 24

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Joint population and strong-lensing inference for resolved gravitational-wave events probes the black-hole merger rate beyond the peak of star formation cites this paper.

Joint population and strong-lensing inference for resolved gravitational-wave events probes the black-hole merger rate beyond the peak of star formation Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 59

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Cosmology in the Einstein Telescope era: comparing traditional and simulation-based methods for population inference cites this paper.

Cosmology in the Einstein Telescope era: comparing traditional and simulation-based methods for population inference Growing Pains: Understanding the Impact of Likelihood Uncertainty on Hierarchical Bayesian Inference for Gravitational-Wave Astronomy

Reference 52

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