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Paper Citation Record · LEDGER

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters

As of 21 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2608.09923.

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

pith.paper-citation-record.v1
2608.09923 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:28:19.651918Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy8
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 216af133-3df2-44e0-867b-1ebef24f80f0 · outbound

This paper cites Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.845931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.601775Z digest=sha256:7d199a46d5e81ccd09add7120426446dcd5e3a81810fc001fa2798e18dc1206b

Observation 5e62fdbf-cd54-4567-b1e3-2c2e83fd640a · outbound

This paper cites Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-11T04:28:19.707159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9f67323d-358a-455b-b094-057a0a386c8a · outbound

This paper cites Constructing an interpretable deep denoiser by unrolling graph Laplacian regularizer,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Constructing an interpretable deep denoiser by unrolling graph Laplacian regularizer,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.833097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.611265Z digest=sha256:3537f9903fb284b379eac5066210141be883d181d1d03c29d7c40308a22c1846

Observation 7337cc3b-667f-46a7-94b4-eecb1db4f238 · outbound

This paper cites Mixed graph signal analysis of joint image denoising / interpolation,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Mixed graph signal analysis of joint image denoising / interpolation,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.817842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.615005Z digest=sha256:9096e02372710fa4d1d0c3a39bbf81e56deae3ca2e76205ca5565df38dc09126

Observation cefcce59-dd9f-4d69-9a9f-835d0a9f5bf9 · outbound

This paper cites an unresolved cited work.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T04:28:19.804335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.619831Z digest=sha256:6223d013a56a29a63e78f13fb07befbc2b30032959067f58bfa3686c0ab81323

Observation 49a9cd50-228e-47ff-ba51-2dbcdf2bd19c · outbound

This paper cites The emerging field of signal processing on graphs,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters The emerging field of signal processing on graphs,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T04:28:19.623538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:28:19.623538Z digest=sha256:beecd3787b28673c48a6e8e98aa74851674928d6baa6f9f5a4f6214a98a85399

Observation 311abee5-ee66-4069-bb34-56342001c1b2 · outbound

This paper cites Wavelets on graphs via spectral graph theory,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Wavelets on graphs via spectral graph theory,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.783521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.627797Z digest=sha256:a4ad84468a1a476064afe85de6740c3e6c0b5e93280805c04401ec57c14bbfff

Observation e8d14313-8344-4ba7-bd4b-373181633794 · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Convolutional neural networks on graphs with fast localized spectral filtering,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.771203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.631590Z digest=sha256:47d652a5646ca33a263ae345b5755b095ec57d2038ff0bfc54976faa5d2bc2c9

Observation 42caa91f-47ec-4bed-9e2b-dbac3c6fe7ee · outbound

This paper cites Interpretable deep image denoiser by unrolling graph Laplacian regularizer,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Interpretable deep image denoiser by unrolling graph Laplacian regularizer,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.759334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.635874Z digest=sha256:205b6f9e36baca18673caf27cc8268552a42f95999edf06e108101737adf454f

Observation b120593e-cb0a-4a5b-a7d7-4e0fdc7e677c · outbound

This paper cites Deep Graph Laplacian Regularization for Robust Denoising of Real Images.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Deep Graph Laplacian Regularization for Robust Denoising of Real Images

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-11T04:28:19.689110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4e3d1975-0898-4a48-a0e4-a979152b6520 · outbound

This paper cites an unresolved cited work.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-11T04:28:19.745605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.643714Z digest=sha256:2d5fd87a8dc67c3cda425e201bfe77a1bb88175a1edc95919f66bf208a9551b1

Observation e71eef3d-dcbb-401a-96d1-ef9400174e9c · outbound

This paper cites Blind estimation of white Gaus- sian noise variance in highly textured images,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Blind estimation of white Gaus- sian noise variance in highly textured images,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.733129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T04:28:19.647602Z digest=sha256:680d1289b733174374761310ad9a56691b25da04982654c4f90e5313a4e8205e

Observation b3948444-e71f-4580-a88e-db858c96c05a · outbound

This paper cites Piecewise polynomial, positive definite and compactly supported radial func- tions of minimal degree,.

Unrolling a Graph-Laplacian Denoiser Realizes Only Compositions of Polynomial Graph Filters Piecewise polynomial, positive definite and compactly supported radial func- tions of minimal degree,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:28:19.719490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

No inbound Pith citation observations are available.