Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.09943.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:57:41.046768Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T20:06:50.304250Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation ec180013-a931-4091-9a21-21f0d4c6cb54 · inbound
DeepWiener: Neural Networks for CMB polarization maps and power spectrum computation Enhancing CMB map reconstruction and power spectrum estimation with convolutional neural networks
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f66651b5-0207-421d-a554-590feeddcdea · inbound
Searching for Inflationary Physics with the CMB Trispectrum: 1. Primordial Theory & Optimal Estimators Enhancing CMB map reconstruction and power spectrum estimation with convolutional neural networks
Reference 229
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f9c3dd3e-6774-4202-8394-a4632f10c6e3 · inbound
Searching for Inflationary Physics with the CMB Trispectrum: 3. Constraints from Planck Enhancing CMB map reconstruction and power spectrum estimation with convolutional neural networks
Reference 114
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 517c8c8d-065a-43a5-9923-475acb99760b · inbound
Deep Learning for CMB Foreground Removal and Beam Deconvolution: A U-Net GAN Approach Enhancing CMB map reconstruction and power spectrum estimation with convolutional neural networks
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.