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Paper Citation Record · LEDGER

Noise Reduction in Gravitational-wave Data via Deep Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2005.06534.

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

pith.paper-citation-record.v1
2005.06534 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T03:33:53.198336Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T03:33:56.402172Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 650be4f9-b590-4998-bfb7-1dc735f31432 · inbound

Nonlinear Independent Component Analysis Scheme and its application to gravitational wave data analysis cites this paper.

Nonlinear Independent Component Analysis Scheme and its application to gravitational wave data analysis Noise Reduction in Gravitational-wave Data via Deep Learning

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T17:36:41.374503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T17:33:37.594218Z digest=sha256:1264a3c0a6d326c97c2764def733c96326dfeb2ba5f2f1a085e36886525d85f2

Observation b85e3577-a99f-4141-aa75-1495a79be484 · inbound

Auto-encoder model for faster generation of effective one-body gravitational waveform approximations cites this paper.

Auto-encoder model for faster generation of effective one-body gravitational waveform approximations Noise Reduction in Gravitational-wave Data via Deep Learning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:10:22.865016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T22:06:32.129237Z digest=sha256:ccf00eab7395859999db9f93b3b2ea988d8155d9a7da51f754f81030a4ce71c6

Observation 48d378b2-f2da-4103-96a2-455ef8dbee6a · 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 Noise Reduction in Gravitational-wave Data via Deep Learning

Reference 125

Resolution
verified exact
arxiv_id, observed 2026-05-21T03:33:56.403631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T03:33:53.198336Z digest=sha256:5720f67224ddb32ecdf7e1732070cbb32d9028c42078de49dbdd7c51f4b63a57