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Paper Citation Record · LEDGER

Complete parameter inference for GW150914 using deep learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2008.03312.

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

pith.paper-citation-record.v1
2008.03312 v1

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measured 0 of 0 reference resolution

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measured 12 of 12 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:33:27.715351Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:14:26.051987Z

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Pith citing papers

Observation f5054c8f-b89f-4bfd-a7a4-5ac6ed863690 · inbound

Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA cites this paper.

Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA Complete parameter inference for GW150914 using deep learning

Reference 154

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arxiv_id, observed 2026-05-24T01:35:56.115221Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3a8522d3-3f04-43c1-bd3b-9dba9f460d6f · inbound

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

Parameter inference of millilensed gravitational waves using neural spline flows Complete parameter inference for GW150914 using deep learning

Reference 56

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arxiv_id, observed 2026-05-19T13:22:18.590240Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ac0fca1f-9f99-4dbe-8860-0d21a9ad1b9b · inbound

Revisiting GW150914 with a non-planar, eccentric waveform model cites this paper.

Revisiting GW150914 with a non-planar, eccentric waveform model Complete parameter inference for GW150914 using deep learning

Reference 160

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no resolver link, observed 2026-08-07T13:33:27.715351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5258dba-a3b9-4ae6-a5dc-d5fdf0b08487 · inbound

Identifying Microlensing by Compact Dark Matter through Diffraction Patterns in Gravitational Waves with Machine Learning cites this paper.

Identifying Microlensing by Compact Dark Matter through Diffraction Patterns in Gravitational Waves with Machine Learning Complete parameter inference for GW150914 using deep learning

Reference 38

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no resolver link, observed 2026-08-05T10:35:01.735201Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:35:01.735201Z digest=sha256:f7a165da17ad52326c1a0c6792412f9886499acafc4504f114052672674ece21

Observation f7c16695-2d84-424c-8be9-d759267c59c0 · inbound

Accelerated inference of microlensed gravitational waves with machine learning cites this paper.

Accelerated inference of microlensed gravitational waves with machine learning Complete parameter inference for GW150914 using deep learning

Reference 62

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no resolver link, observed 2026-08-03T22:55:47.691065Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:55:47.691065Z digest=sha256:847c0ad0bb895e049e1cff3a2ceb169e3c4321d5665b409cb36faeb1ac2efeab

Observation 5a666a18-7918-4051-ba96-f915216fa56f · inbound

Accelerating parameter estimation for parameterized tests of general relativity with gravitational-wave observations cites this paper.

Accelerating parameter estimation for parameterized tests of general relativity with gravitational-wave observations Complete parameter inference for GW150914 using deep learning

Reference 33

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verified exact
arxiv_id, observed 2026-05-17T21:30:17.858809Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T21:28:45.671170Z digest=sha256:5b5389de4e02329727dc6a2fc1140a4e9618ecc0d7f2bc63ddc89cf8aacc6404

Observation 34d0a2ab-dd4e-4c50-8fe6-5d02238b80fb · inbound

Flexible Gravitational-Wave Parameter Estimation with Transformers cites this paper.

Flexible Gravitational-Wave Parameter Estimation with Transformers Complete parameter inference for GW150914 using deep learning

Reference 20

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no resolver link, observed 2026-08-03T18:59:10.393322Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:59:10.393322Z digest=sha256:ab15344246a0b125f6e281b05f030ea86ee41adee53c533cdd96c2ae8adadb99

Observation 95a7dfff-178c-403e-9527-d2f70c664a87 · inbound

Discovering gravitational waveform distortions from lensing: A deep dive into GW231123 cites this paper.

Discovering gravitational waveform distortions from lensing: A deep dive into GW231123 Complete parameter inference for GW150914 using deep learning

Reference 40

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no resolver link, observed 2026-08-03T15:28:14.485096Z

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Observation fbb21ef0-67d5-4891-8a8f-9b2fbbf59766 · inbound

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection cites this paper.

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection Complete parameter inference for GW150914 using deep learning

Reference 124

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verified exact
arxiv_id, observed 2026-05-21T03:33:56.275675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T03:33:53.198336Z digest=sha256:3827aaccd6bbb15d016bc1a9bd44cd97958b34a380762bf6fdd620773f4dbb0c

Observation a5db1f33-d0b7-47a9-b69a-f4d5846cfeca · inbound

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

Fortifying gravitational-wave population inference with normalizing flows Complete parameter inference for GW150914 using deep learning

Reference 57

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unresolved
no resolver link, observed 2026-08-02T11:36:01.615522Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:36:01.615522Z digest=sha256:a9c1bbed8504e75120741bda99062015de72b0f40b5b0a75f64784d1143115da

Observation 2db939c4-d49e-4111-8c38-7f6fd94042d4 · inbound

Neural posterior estimation of Galactic Binary signals for the LISA mission cites this paper.

Neural posterior estimation of Galactic Binary signals for the LISA mission Complete parameter inference for GW150914 using deep learning

Reference 31

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verified exact
arxiv_id, observed 2026-06-30T08:14:26.053728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 76a724eb-007c-4b20-96aa-fb2c4cde1119 · inbound

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

Identifying lensed gravitational waves with physics-informed posterior learning Complete parameter inference for GW150914 using deep learning

Reference 151

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unresolved
no resolver link, observed 2026-07-11T23:16:00.672720Z

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Unavailable: canonical work link unavailable.

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