Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Noise Reduction in Gravitational-wave Data via Deep Learning
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2005.06534.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T04:49:37.911065Z
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
- verified exact0
- 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 29a240d7-0d07-423a-92c6-7aaaea81afda · inbound
Adaptive cancellation of mains power interference in continuous gravitational wave searches with a hidden Markov model cites this paper.
Adaptive cancellation of mains power interference in continuous gravitational wave searches with a hidden Markov model Noise Reduction in Gravitational-wave Data via Deep Learning
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T04:49:37.911065Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ee39c63-62e4-4231-b853-e7af5c677b80 · inbound
A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run cites this paper.
A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run Noise Reduction in Gravitational-wave Data via Deep Learning
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:54:52.009729Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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 2026-08-13T06:32:02.005865+00:00.
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 2026-08-13T06:32:02.005865+00:00.
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 2026-08-13T06:32:02.005865+00:00.