Paper Citation Record · LEDGER

An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2212.08674.

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

pith.paper-citation-record.v1
2212.08674 v3

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 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:14:51.454932Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:58:54.693773Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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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 9abbaec6-2d42-4adb-82f6-8b70f56d6211 · inbound

High-Dimensional Unfolding in Large Backgrounds cites this paper.

High-Dimensional Unfolding in Large Backgrounds An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:51.454932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dec90129-b358-48e8-8219-03db22ac3ec5 · inbound

Simulation-Prior Independent Neural Unfolding Procedure cites this paper.

Simulation-Prior Independent Neural Unfolding Procedure An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:38.324405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7bc2a84-995c-4686-b8d1-3ad5f7d41b3d · inbound

Toward an event-level analysis of hadron structure using differential programming cites this paper.

Toward an event-level analysis of hadron structure using differential programming An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T15:29:53.359423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8b1594-67fd-43c6-b547-03174b40c533 · inbound

Reweighting Adversarial Networks for Unbinned Unfolding cites this paper.

Reweighting Adversarial Networks for Unbinned Unfolding An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:27:03.807555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b729c1dd-e3d0-4316-b5c2-2e461fa54ec9 · inbound

Local Conformal Predictions for Calibrated Surrogates cites this paper.

Local Conformal Predictions for Calibrated Surrogates An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:58:54.695063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fdc5c206-85ee-4c2b-b564-b48dceee8560 · inbound

An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning cites this paper.

An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-01T07:01:00.757020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.