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Paper Citation Record · LEDGER

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems

As of 15 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2502.05127.

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

pith.paper-citation-record.v1
2502.05127 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:14:34.593506Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:15:02.198097Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:15:07.211680Z

Reference resolution

21 of 21 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 63570ed4-ddb5-4031-8a50-29bc2dccb921 · outbound

This paper cites Kaipio and E.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Kaipio and E

Reference 1

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Observation 251256bd-6ada-4246-bbf0-8cac5f0559e6 · outbound

This paper cites Efficient bayesian computation by proximal markov chain monte carlo: When langevin meets moreau,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Efficient bayesian computation by proximal markov chain monte carlo: When langevin meets moreau,

Reference 2

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Observation fb1aeb1a-194a-433d-a9bb-7b9e015f0306 · outbound

This paper cites Maximum-a-posteriori estimation with bayesian confidence re- gions,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Maximum-a-posteriori estimation with bayesian confidence re- gions,

Reference 3

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Observation 82c1e1fa-672e-4151-9b7a-fd24acf6dcd4 · outbound

This paper cites Bayesian imaging using plug & play priors: when langevin meets tweedie,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Bayesian imaging using plug & play priors: when langevin meets tweedie,

Reference 4

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Observation 0a1d10e9-0577-4f42-b897-9a6faf39e1f9 · outbound

This paper cites Bayesian imaging with data- driven priors encoded by neural networks,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Bayesian imaging with data- driven priors encoded by neural networks,

Reference 5

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Observation fb7a30f2-f880-433f-b19a-854b0085a2c7 · outbound

This paper cites Do Bayesian imaging methods report trustworthy probabilities?.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Do Bayesian imaging methods report trustworthy probabilities?

Reference 6

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Source-reported events for the cited work

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Observation 48068b58-01a9-48e6-90a3-3f1b9d666bac · outbound

This paper cites Equivariant bootstrapping for uncertainty quantification in imaging inverse problems,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Equivariant bootstrapping for uncertainty quantification in imaging inverse problems,

Reference 7

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Observation 6748eb7e-5ace-4910-b70c-ca51034638a0 · outbound

This paper cites Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry

Reference 8

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Observation e2304895-677e-42dc-8544-2a0ca2ac673e · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 9

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Source-reported events for the cited work

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Observation 5fa77b53-04b1-4947-9b6f-d5fd3013e49d · outbound

This paper cites Posterior-variance– based error quantification for inverse problems in imaging,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Posterior-variance– based error quantification for inverse problems in imaging,

Reference 10

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Observation 1cdd144e-15e0-448a-8a12-3f1e5f97eef6 · outbound

This paper cites Conformal uncertainty sets for robust optimiza- tion,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Conformal uncertainty sets for robust optimiza- tion,

Reference 11

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Observation 816abff6-1c7f-4fd7-95a4-004edb6123f5 · outbound

This paper cites Estimation of the mean of a multivariate normal distribution,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Estimation of the mean of a multivariate normal distribution,

Reference 12

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Observation a74453b6-34b3-420e-86c9-ffc4e4bf7a26 · outbound

This paper cites Second-order stein: Sure for sure and other applications in high-dimensional inference,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Second-order stein: Sure for sure and other applications in high-dimensional inference,

Reference 13

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Observation e09a20ec-1b69-412b-97ea-890c07f6a7ba · outbound

This paper cites Unbiased risk estimates for singular value thresholding and spectral estimators,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Unbiased risk estimates for singular value thresholding and spectral estimators,

Reference 14

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Observation e4b58af4-2411-4b5d-af16-1556832dac53 · outbound

This paper cites Degrees of freedom in lasso problems,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Degrees of freedom in lasso problems,

Reference 15

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Observation f28d4ace-e16c-485e-9525-13c17b381832 · outbound

This paper cites Monte-Carlo SURE: A black-box op- timization of regularization parameters for general denoising algorithms,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Monte-Carlo SURE: A black-box op- timization of regularization parameters for general denoising algorithms,

Reference 16

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Observation 2fb3889c-f46b-48cf-acfa-25ae0e0ffbbd · outbound

This paper cites On divergence ap- proximations for unsupervised training of deep denoisers based on stein’s unbiased risk estimator,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems On divergence ap- proximations for unsupervised training of deep denoisers based on stein’s unbiased risk estimator,

Reference 17

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Source-reported events for the cited work

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Observation a768a529-7daa-428e-9e74-6d166ca9827c · outbound

This paper cites Ntire 2017 challenge on single image super- resolution: Dataset and study,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Ntire 2017 challenge on single image super- resolution: Dataset and study,

Reference 18

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Source-reported events for the cited work

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Observation ad7af6fe-3cb7-44d8-821f-065d7b1fa466 · outbound

This paper cites Plug- and-play imagerestorationwith deepdenoiserprior,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Plug- and-play imagerestorationwith deepdenoiserprior,

Reference 19

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Source-reported events for the cited work

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Observation f35bbc69-077b-485c-8368-61c4c13fd28b · outbound

This paper cites UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate

Reference 20

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Source-reported events for the cited work

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Observation a4cae068-0dd2-41cb-accd-c1537c3436b3 · outbound

This paper cites Poly- blur: Removing mild blur by polynomial reblurring,.

Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems Poly- blur: Removing mild blur by polynomial reblurring,

Reference 21

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Pith citing papers

Observation ed06236c-8917-43c6-854d-dec04e99c210 · inbound

Hypothesis Testing in Imaging Inverse Problems cites this paper.

Hypothesis Testing in Imaging Inverse Problems Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems

Reference 15

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