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Paper Citation Record · LEDGER

How to quantify fields or textures? A guide to the scattering transform

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2112.01288.

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

pith.paper-citation-record.v1
2112.01288 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:44:27.440495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:07:51.211636Z

Reference resolution

0 of 0 outbound references displayed

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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 33b2483c-02e5-46a1-83a5-8c840731795d · inbound

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network cites this paper.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network How to quantify fields or textures? A guide to the scattering transform

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T23:05:15.517726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T23:05:15.517726Z digest=sha256:58198cd21d412e3387f93851b352c7ab6d4d45da1065974fa26da293f6510aa3

Observation 3f7d25cf-be14-4161-bb5e-2b72beda0e14 · inbound

Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps cites this paper.

Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps How to quantify fields or textures? A guide to the scattering transform

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-16T04:44:27.440495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6e4ef471-c936-4667-8ade-5dd9c566b764 · inbound

Characterizing Ocean Flows with the Scattering Transform cites this paper.

Characterizing Ocean Flows with the Scattering Transform How to quantify fields or textures? A guide to the scattering transform

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-16T04:39:33.793357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 560ac964-851e-41a9-a507-1a3399133d4d · inbound

Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform cites this paper.

Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform How to quantify fields or textures? A guide to the scattering transform

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:51.943073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:30:51.943073Z digest=sha256:587ff1c43b3366aa508a8280e3c5fc48ad450c5c851e8fb2ab7694d7e451d001

Observation 462e6879-d513-4cb0-9172-274a0409d732 · inbound

Machine-learning applications for weak-lensing cosmology cites this paper.

Machine-learning applications for weak-lensing cosmology How to quantify fields or textures? A guide to the scattering transform

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:07:51.214919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T19:06:06.290441Z digest=sha256:cd979594b33238208e062a00d017e53e9b9a33611e8c1fb82c365764e4747bc5

Observation 225c0272-637d-4c3b-9e9d-a807a0994716 · inbound

Multi-branch classification of diffuse cluster radio emission cites this paper.

Multi-branch classification of diffuse cluster radio emission How to quantify fields or textures? A guide to the scattering transform

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-31T10:31:11.787272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T10:31:11.787272Z digest=sha256:984ece8184fdfac3e6b30299249ef7effb889050aa87e8d2e99c5e659b82bea0