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Paper Citation Record · LEDGER

Gravitational wave populations and cosmology with neural posterior estimation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2311.12093.

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pith.paper-citation-record.v1
2311.12093 v2

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measured 12 of 12 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:23:01.682073Z

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A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T13:22:18.476103Z

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Outbound references

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Pith citing papers

Observation 5321f870-75b1-4dcb-adcc-e47cd355a2a4 · inbound

A fast deep-learning approach to probing primordial black hole populations in gravitational wave events cites this paper.

A fast deep-learning approach to probing primordial black hole populations in gravitational wave events Gravitational wave populations and cosmology with neural posterior estimation

Reference 34

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Observation 4ce1411e-bd11-4348-a732-375ca12d9d3c · inbound

Parameter inference of millilensed gravitational waves using neural spline flows cites this paper.

Parameter inference of millilensed gravitational waves using neural spline flows Gravitational wave populations and cosmology with neural posterior estimation

Reference 66

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arxiv_id, observed 2026-05-19T13:22:18.493518Z

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Observation 6fe0c24e-9e93-4de2-8da8-ea71469382a2 · inbound

Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop cites this paper.

Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop Gravitational wave populations and cosmology with neural posterior estimation

Reference 75

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Observation fc5d357f-8ca9-4b78-a46c-8d9d133c9a90 · inbound

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 Gravitational wave populations and cosmology with neural posterior estimation

Reference 18

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arxiv_id, observed 2026-05-19T04:37:03.802440Z

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Observation a9fea4fc-fbfa-4ad9-bd9e-c124c3c44b9e · inbound

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 Gravitational wave populations and cosmology with neural posterior estimation

Reference 102

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Observation 5daa8210-9182-44c2-a864-ec7530fe5e73 · inbound

An Implementation to Identify the Properties of Multiple Population of Gravitational Wave Sources cites this paper.

An Implementation to Identify the Properties of Multiple Population of Gravitational Wave Sources Gravitational wave populations and cosmology with neural posterior estimation

Reference 64

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arxiv_id, observed 2026-05-18T17:06:39.224147Z

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Observation c94c1cb6-8aff-4696-9c13-30b8b96f7b2d · inbound

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 Gravitational wave populations and cosmology with neural posterior estimation

Reference 98

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arxiv_id, observed 2026-05-16T05:37:24.033650Z

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Observation cb3a4dcf-87ee-44e3-983d-9dbfeab9e0b0 · inbound

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows cites this paper.

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows Gravitational wave populations and cosmology with neural posterior estimation

Reference 100

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arxiv_id, observed 2026-05-10T12:45:24.093990Z

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Observation 200987f4-c13d-49f6-a771-417f15345a2f · inbound

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 Gravitational wave populations and cosmology with neural posterior estimation

Reference 28

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arxiv_id, observed 2026-05-13T02:02:06.075255Z

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Observation 1fc0a3ee-aefd-4f5d-ac77-525228402bdd · inbound

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

Fortifying gravitational-wave population inference with normalizing flows Gravitational wave populations and cosmology with neural posterior estimation

Reference 79

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Observation 7bef4268-3ba5-4be1-b010-9f781030b7f5 · inbound

Identifying lensed gravitational waves with physics-informed posterior learning cites this paper.

Identifying lensed gravitational waves with physics-informed posterior learning Gravitational wave populations and cosmology with neural posterior estimation

Reference 157

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Observation 972d9cd4-47d0-4b51-8fd9-ea2cbc8f640f · inbound

Unified remnant models for aligned-spin, precessing, and eccentric binary black hole mergers cites this paper.

Unified remnant models for aligned-spin, precessing, and eccentric binary black hole mergers Gravitational wave populations and cosmology with neural posterior estimation

Reference 133

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