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Paper Citation Record · LEDGER

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems

As of 20 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 1 inbound Pith citation observation for arXiv:2505.09528.

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

pith.paper-citation-record.v1
2505.09528 v1

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:34:57.846170Z

measured 80 of 80 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T06:10:51.218938Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T06:12:25.994887Z

Reference resolution

79 of 79 outbound references displayed

  • verified exact2
  • verified fuzzy56
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92faf6c6-5cd8-46bb-88c2-79d909f725a6 · outbound

This paper cites Deep Bayesian Inversion.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Deep Bayesian Inversion

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.427566Z digest=sha256:a3ab29719cb9c479dbe9c44b759d4c3e11dc4abb0f066d3526218943858e8a11

Observation cb00e69e-94d5-4f6f-8699-e5e8bc5d9e54 · outbound

This paper cites Andersen, Joachim Dahl, and Lieven Vandenberghe.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Andersen, Joachim Dahl, and Lieven Vandenberghe

Reference 2

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verified fuzzy
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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 c2899a43-e42d-4885-9f7c-799e0be4db82 · outbound

This paper cites Angelopoulos and Stephen Bates.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Angelopoulos and Stephen Bates

Reference 3

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unresolved
no resolver link, observed 2026-08-15T21:34:57.438905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0fe744b6-4a5c-4af6-9760-d8a03cc48533 · outbound

This paper cites Conformal Risk Control.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conformal Risk Control

Reference 4

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unresolved
no resolver link, observed 2026-08-15T21:34:57.444433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 63145bf0-bf79-45c0-bf00-275ad9bccf38 · outbound

This paper cites Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging

Reference 5

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unresolved
no resolver link, observed 2026-08-15T21:34:57.450260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 00582372-5ec6-4f2f-b74c-a1cc5bd5a02a · outbound

This paper cites O ktem, and Carola-Bibiane Sch \.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems O ktem, and Carola-Bibiane Sch \

Reference 6

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verified fuzzy
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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 bd03800d-e715-4249-8fd3-7c1f73b3196a · outbound

This paper cites an unresolved cited work.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Unresolved cited work

Reference 7

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verified exact
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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 369d51e7-192f-42de-a430-df2059bd1c9b · outbound

This paper cites Quantifying model uncertainty in inverse problems via B ayesian deep gradient descent.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Quantifying model uncertainty in inverse problems via B ayesian deep gradient descent

Reference 8

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no resolver link, observed 2026-08-15T21:34:57.466164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.466164Z digest=sha256:7d593c0bd337fecddcc898f5ef6095f578a623bb02c60bed9cde3269081e3049

Observation 731e5b46-ee92-465b-b77d-bd44bd121ce6 · outbound

This paper cites Conformal prediction beyond exchangeability.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conformal prediction beyond exchangeability

Reference 9

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verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.470940Z digest=sha256:601c9dd927d4dedf068f00a1ef70019a17b8276e0f5e059ee7c221e8bebeac12

Observation 64c7062d-ac37-4b6d-b26c-883855395004 · outbound

This paper cites Distribution-free, risk-controlling prediction sets.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Distribution-free, risk-controlling prediction sets

Reference 10

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unresolved
no resolver link, observed 2026-08-15T21:34:57.475699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 512241f8-040a-428b-91a2-c975ae156c35 · outbound

This paper cites Principal uncertainty quantification with spatial correlation for image restoration problems.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Principal uncertainty quantification with spatial correlation for image restoration problems

Reference 11

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verified fuzzy
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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 17af6d30-ee57-41ef-a071-646912d892b8 · outbound

This paper cites Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction

Reference 12

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verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.490036Z digest=sha256:36ae7a2490a331f849f505dc8b9de51082c187f85de6ddf95ef1f5eb17bfb3af

Observation ba331527-0d7b-4642-9a21-71555aa098e3 · outbound

This paper cites A regularized conditional GAN for posterior sampling in inverse problems.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems A regularized conditional GAN for posterior sampling in inverse problems

Reference 13

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verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.494841Z digest=sha256:b14621e4ce26abb62cd4228b507bbeeb99849180c66257f14461635afa503883

Observation beec9af8-1206-4542-9cb6-a54841f3aae2 · outbound

This paper cites On hallucinations in tomographic image reconstruction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems On hallucinations in tomographic image reconstruction

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.283998Z

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=arxiv_source observed=2026-08-15T21:34:57.499709Z digest=sha256:4be5cf565cbf7fe8a213fc2f08b49c71a2980da815e91a027ba0348174f8c564

Observation f857e2d3-9c58-460f-9c32-3741455ef92f · outbound

This paper cites The perception-distortion tradeoff.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The perception-distortion tradeoff

Reference 15

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verified fuzzy
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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 a804544f-4d51-403b-8375-051e931aa5a1 · outbound

This paper cites Torchmetrics, 2022.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Torchmetrics, 2022

Reference 16

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.510043Z digest=sha256:a1a7934c5783d3781e45917c287de5d74e7082928594fe218e59fd82d6abfacb

Observation c3eba909-ee42-452e-b448-1efa9bd52860 · outbound

This paper cites Oppenheimer, Abhishek Pandala, Juan José Quiroz Omaña, Nikitas Rontsis, Paarth Shah, Samuel St-Jean, Nicola Vitucci, Soeren Wolfers, and Fengyu Yang.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Oppenheimer, Abhishek Pandala, Juan José Quiroz Omaña, Nikitas Rontsis, Paarth Shah, Samuel St-Jean, Nicola Vitucci, Soeren Wolfers, and Fengyu Yang

Reference 17

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.515021Z digest=sha256:43d695a82f0ae159e0bab83dce8984ab67cf2655061c9f221cc6401bab0cbd40

Observation 8c38281b-98a4-4266-9a8a-0472307c8b6e · outbound

This paper cites Robust validation: C onfident predictions even when distributions shift.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Robust validation: C onfident predictions even when distributions shift

Reference 18

Resolution
verified fuzzy
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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 b7c3caf5-d31b-4f95-804a-d2c01b41528d · outbound

This paper cites XGBoost: A scalable tree boosting system.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems XGBoost: A scalable tree boosting system

Reference 19

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.526199Z digest=sha256:436c31d239e6fafce4349196fb76e0f73bd1dc30c528c46d64727d5169b7a083

Observation 4b9b54fc-5887-485e-8f4f-f88a630e4731 · outbound

This paper cites The potential dangers of artificial intelligence for radiology and radiologists.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The potential dangers of artificial intelligence for radiology and radiologists

Reference 20

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.532945Z digest=sha256:ca8ee8d56449029cab61af42d1f84e7bb1d8c76404c749c6873e640ce5a52fc8

Observation 1efd16bb-06ee-428d-b1be-b1da02d42487 · outbound

This paper cites Distribution matching losses can hallucinate features in medical image translation.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Distribution matching losses can hallucinate features in medical image translation

Reference 21

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.538488Z digest=sha256:d9cad804e2ce5a6479eba412d7b28984beb5253465d9d2156ce03cc5d61c457d

Observation 4e985158-f3d3-4823-bcf7-1c634a93663b · outbound

This paper cites Image quality assessment: U nifying structure and texture similarity.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Image quality assessment: U nifying structure and texture similarity

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.155851Z

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=arxiv_source observed=2026-08-15T21:34:57.543718Z digest=sha256:fae6832cbcbbe144b2e242638abc1577e8c353712a661ffdf860e4650f64cb48

Observation b5228084-545a-40f2-9c37-e33e652fff78 · outbound

This paper cites Simoncelli.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Simoncelli

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.138998Z

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=arxiv_source observed=2026-08-15T21:34:57.548970Z digest=sha256:9785e665540981e59ea2844229718b73717488ec9a32b471deb368fddc047b75

Observation c514b03c-9e92-4278-aaa1-abf8a34d7635 · outbound

This paper cites Efficient B ayesian computation by proximal M arkov chain M onte C arlo: W hen L angevin meets M oreau.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Efficient B ayesian computation by proximal M arkov chain M onte C arlo: W hen L angevin meets M oreau

Reference 24

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-15T21:34:57.554531Z digest=sha256:19ab5088debfaf17431ddd96b7a7bc9254a1f9cbd9385e827633669aa2df8687

Observation c99c38d0-3ab4-4cff-9b50-2bf1284ad27e · outbound

This paper cites Uncertainty quantification in deep MRI reconstruction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Uncertainty quantification in deep MRI reconstruction

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.103951Z

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=arxiv_source observed=2026-08-15T21:34:57.559586Z digest=sha256:6192bdb810caf2ae036e7bffd6f39ff6a62cf5529f8fe1e05f5455f6f52eb38f

Observation adfa7e7a-db00-45b2-aa26-14d97ce351cd · outbound

This paper cites Uncertainty quantification for deep unrolling-based computational imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Uncertainty quantification for deep unrolling-based computational imaging

Reference 26

Resolution
metadata mismatch
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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=arxiv_source observed=2026-08-15T21:34:57.564545Z digest=sha256:4c1148c0da7aae5f89ce75f358f9c48b27ac8b0453eab1bd9938aeabc4ae094a

Observation 895d93a3-22f8-4da2-a44c-690e2c399e0b · outbound

This paper cites Quantifying generative model uncertainty in posterior sampling methods for computational imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Quantifying generative model uncertainty in posterior sampling methods for computational imaging

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.087806Z

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=arxiv_source observed=2026-08-15T21:34:57.569591Z digest=sha256:1b4cc1ab0c4a131c331d0ebb201d56f917a6d12e015c4bc4b992c4c683827171

Observation 4b17988b-9c40-46af-824f-8141d6b95f04 · outbound

This paper cites Pytorch lightning, 2019.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Pytorch lightning, 2019

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.072117Z

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=arxiv_source observed=2026-08-15T21:34:57.574622Z digest=sha256:7c2a59a84ae690bd86666ba69c0beec4e02be418467e03e125b0a40f2bfd235c

Observation 0813961f-bc1b-4613-a080-96388e37b209 · outbound

This paper cites A Modern Approach to Probability Theory.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems A Modern Approach to Probability Theory

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.055839Z

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=arxiv_source observed=2026-08-15T21:34:57.579418Z digest=sha256:0def60cf8e48357a54d846960b54df81b6428fd38532d7f2c45868c3d0aac6aa

Observation 5495b535-d683-4c51-aea3-35aee198551b · outbound

This paper cites The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.585343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.585343Z digest=sha256:d68bb658e04b82e3835d4482829d02c33703e1dda8a35d5a9ff11d1923689fb0

Observation 8aa982bc-c49c-4978-a031-d4167ab6ab69 · outbound

This paper cites Physics-driven deep learning for computational magnetic resonance imaging: C ombining physics and machine learning for improved medical imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Physics-driven deep learning for computational magnetic resonance imaging: C ombining physics and machine learning for improved medical imaging

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.039399Z

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=arxiv_source observed=2026-08-15T21:34:57.590844Z digest=sha256:c7e1ccd7b551ea511acc721f9cb0ab7d25fc2a7100a278d9e087a20d4744e72e

Observation 529e376a-a35e-406d-b838-ab81ecc3c291 · outbound

This paper cites Denoising diffusion probabilistic models.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Denoising diffusion probabilistic models

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.022935Z

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=arxiv_source observed=2026-08-15T21:34:57.595819Z digest=sha256:97c1eef94dd4cbacd5343e2a7b7a5e0cdb2b51b62079c1e847b358fb1a48fe3f

Observation 4d18b9e6-cf41-441c-ac6b-9cd63a42d12d · outbound

This paper cites The promise and peril of deep learning in microscopy.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The promise and peril of deep learning in microscopy

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:59.005179Z

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=arxiv_source observed=2026-08-15T21:34:57.600824Z digest=sha256:3497bc9d04863ebd0feb39181acf74e958211e73a1415c60836d08c4faa7ab7f

Observation befa2130-3d73-446d-9a6d-f7413d2e849b · outbound

This paper cites Conffusion: Confidence Intervals for Diffusion Models.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conffusion: Confidence Intervals for Diffusion Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.606082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.606082Z digest=sha256:b179ac128e8a706a89243347a927544fb8f90e34e949efbb818ff9a78aad452b

Observation 9bb08fdb-6546-42cc-a58f-b6fedd186b5b · outbound

This paper cites Robust compressed sensing MRI with deep generative priors.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Robust compressed sensing MRI with deep generative priors

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.988944Z

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=arxiv_source observed=2026-08-15T21:34:57.612126Z digest=sha256:daf3c966954dc377ea323610634e193c65dd88883834e2e8b36c45dfa158b90b

Observation 6ee41398-9a34-4276-8821-57013c6fe735 · outbound

This paper cites Technical Report (v1.0)--Pseudo-random Cartesian Sampling for Dynamic MRI.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Technical Report (v1.0)--Pseudo-random Cartesian Sampling for Dynamic MRI

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.616990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.616990Z digest=sha256:cd1b625b9c85d7e22b902d57f021b3bd85228f3b3fb7231850f3b753cb6f185c

Observation 6c4a4c8a-94dd-4158-ae32-a6a7d5ee6d6f · outbound

This paper cites Progressive growing of GAN s for improved quality, stability, and variation.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Progressive growing of GAN s for improved quality, stability, and variation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.972618Z

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=arxiv_source observed=2026-08-15T21:34:57.622782Z digest=sha256:6ad84839ddbb620e4bd4ae2b3483fc94f1ac6b67276348c191c6196333195a1a

Observation 604ee242-0e47-46ce-b343-b1cdb5a9a352 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems A style-based generator architecture for generative adversarial networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.957130Z

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=arxiv_source observed=2026-08-15T21:34:57.627736Z digest=sha256:b3969aad746b09d844dd0528292401c89f163332d746d6c071936b78145b1591

Observation 327779a5-d6b0-4f02-a50e-b58cc9fdbdea · outbound

This paper cites Image quality assessment for magnetic resonance imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Image quality assessment for magnetic resonance imaging

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.939476Z

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=arxiv_source observed=2026-08-15T21:34:57.633014Z digest=sha256:52718892b0876781bf85c8ac3b25ec4be28ffeade97a78b2e47e90ed8be4e44b

Observation 1e6a09b8-0f41-4422-a21f-541f3a07a991 · outbound

This paper cites Denoising diffusion restoration models.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Denoising diffusion restoration models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.920239Z

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=arxiv_source observed=2026-08-15T21:34:57.638719Z digest=sha256:ac90251793fa761732eecb767e7a81090995ab8602cb4519be6231f386d9115a

Observation 6b6844ba-e59f-4ef0-b855-e5eedc92a641 · outbound

This paper cites Denoising diffusion restoration models.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Denoising diffusion restoration models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.902501Z

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=arxiv_source observed=2026-08-15T21:34:57.643849Z digest=sha256:7de26ed2620c3a541463bf348ec7094883729b08b57bc8de9508e39b3eb68b22

Observation 4b04029d-9a03-4662-a71f-d247baca29b9 · outbound

This paper cites What uncertainties do we need in B ayesian deep learning for computer vision? In Proc.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems What uncertainties do we need in B ayesian deep learning for computer vision? In Proc

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.886275Z

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=arxiv_source observed=2026-08-15T21:34:57.648632Z digest=sha256:c92d54c9a281e85b8a769da9e411bd4fc88bbf8162dc748c495b117b5f3cb9fb

Observation 5df5ce5d-e38f-4250-998d-44697e4bfd3b · outbound

This paper cites Deep-learning methods for parallel magnetic resonance imaging reconstruction: A survey of the current approaches, trends, and issues.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Deep-learning methods for parallel magnetic resonance imaging reconstruction: A survey of the current approaches, trends, and issues

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.870019Z

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=arxiv_source observed=2026-08-15T21:34:57.653988Z digest=sha256:15155b934ff85fd6d695249f75f0af26a5b6b58aaaa13e997f11d0f6c1bf8b85

Observation 70a3cbc8-bbf7-4e74-85d8-b60c9067d32b · outbound

This paper cites Regression quantiles.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Regression quantiles

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.658838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.658838Z digest=sha256:7cc90b291efc571f7c155489ede77c60dd1fd6d0b3f9d23d7ea23514e792d9e5

Observation 96442b4f-c5fe-491c-aa38-3810146a8477 · outbound

This paper cites Conformal prediction masks: V isualizing uncertainty in medical imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conformal prediction masks: V isualizing uncertainty in medical imaging

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.853382Z

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=arxiv_source observed=2026-08-15T21:34:57.664018Z digest=sha256:06265ab1e094c9897dac93dd54113f9396735c36695cd79f892c9243759b2a5b

Observation 40969b46-fd72-4aea-8143-7fc9b09c7848 · outbound

This paper cites Bayesian imaging using plug & play priors: W hen L angevin meets T weedie.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Bayesian imaging using plug & play priors: W hen L angevin meets T weedie

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.836295Z

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=arxiv_source observed=2026-08-15T21:34:57.669032Z digest=sha256:109bf0d0a1d84aa1e181b9aed866da79a46a0065676640be5ae113c3c0aca6e7

Observation faf372c4-0113-42dc-9476-ee730f4a854e · outbound

This paper cites Distribution-free prediction bands for non-parametric regression.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Distribution-free prediction bands for non-parametric regression

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.674092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.674092Z digest=sha256:16fb62f6b5b331c5915e91bfe4478c4710260fe4a7b52ed9a884fb89edaa339c

Observation 524ccd99-e20c-4bec-ac61-9b979bf62ae9 · outbound

This paper cites Tibshirani, and Larry Wasserman.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Tibshirani, and Larry Wasserman

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.818425Z

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=arxiv_source observed=2026-08-15T21:34:57.678831Z digest=sha256:7708f33d7108d544808095a4851808e17f2c0c17737806e1cda2babc83f61fef

Observation 371c8503-4b3a-4211-9945-63edf9ce9f7e · outbound

This paper cites Perceptual visual quality metrics: A survey.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Perceptual visual quality metrics: A survey

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.801856Z

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=arxiv_source observed=2026-08-15T21:34:57.683548Z digest=sha256:d9752131f2ad24ffa10fd213f933c9bbb19cabbd6546932ce7ee6a978391ebcc

Observation e2a6feb5-c208-461b-b9d2-6d917f150c60 · outbound

This paper cites Convolutional neural networks as a model of the visual system: P ast, present, and future.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Convolutional neural networks as a model of the visual system: P ast, present, and future

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.784023Z

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=arxiv_source observed=2026-08-15T21:34:57.688231Z digest=sha256:cf6cbdcb1d3e2b11c5b552e1159db371cede6d7f73e5720eb6c87cba8f6607c0

Observation a5abf614-876d-4c2c-8eeb-d6e82b4391cb · outbound

This paper cites Results of the 2020 fastMRI challenge for machine learning MR image reconstruction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Results of the 2020 fastMRI challenge for machine learning MR image reconstruction

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.765866Z

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=arxiv_source observed=2026-08-15T21:34:57.693419Z digest=sha256:2a322a26ce86a03cb30fb08fcbde89de7cfeaf8a2c9526716d232aea65b341b5

Observation ec8ddacd-cc21-4487-9f35-f5657fe44f9a · outbound

This paper cites Bayesian uncertainty estimation of learned variational MRI reconstruction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Bayesian uncertainty estimation of learned variational MRI reconstruction

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.749153Z

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=arxiv_source observed=2026-08-15T21:34:57.698358Z digest=sha256:67e8cad10d98ca46a71f003d0287730c413499593b7a98513a39aefd510457de

Observation cd20fad6-c313-45e8-9e69-aac49a192bb9 · outbound

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

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Posterior-variance-based error quantification for inverse problems in imaging

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.730531Z

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=arxiv_source observed=2026-08-15T21:34:57.703182Z digest=sha256:b3d31e042987312fb4cf755c13e12450e1d10e3961ecceb941b97eb2be241fa2

Observation 34b7a7de-f6f4-4c9c-8ebe-cb8f53441fe0 · outbound

This paper cites Inductive confidence machines for regression.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Inductive confidence machines for regression

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.708003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.708003Z digest=sha256:37de8770a7db6f98a608892925c1a309c3d4c12bb1c802c36762f6dc98af1915

Observation a3cfdb31-2248-420e-9d1e-31672a54ca11 · outbound

This paper cites PyTorch: A n imperative style, high-performance deep learning library.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems PyTorch: A n imperative style, high-performance deep learning library

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.712326Z

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=arxiv_source observed=2026-08-15T21:34:57.713874Z digest=sha256:cf1fc0c8408703d70708be93d648976132dda0cadd7101118299e0dfbc765ea1

Observation 673f5d11-a69a-49df-b463-d17f85d387e2 · outbound

This paper cites The NMR phased array.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The NMR phased array

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.693381Z

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=arxiv_source observed=2026-08-15T21:34:57.719720Z digest=sha256:269e1c883a6679115daaae2835f1427d545b3406d0701197ae72b861a74e8442

Observation eee6b8f5-4821-4443-a94b-f27c9616e45f · outbound

This paper cites Conformalized Quantile Regression.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conformalized Quantile Regression

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.726151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.726151Z digest=sha256:23068b521688427bcbfb457439ab50e2b3c10356d47e649cef4a12cf8c3235ab

Observation 6ae6f145-f76c-435d-b76b-aa88280a5351 · outbound

This paper cites Semantic uncertainty intervals for disentangled latent spaces.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Semantic uncertainty intervals for disentangled latent spaces

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T21:34:57.732535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:34:57.732535Z digest=sha256:4b39f53ef6e67d2e8984b0cf3cbe4789b81bcf1e7f2e508af0f9b8e5071a7a13

Observation b570dd69-6c7d-44ae-a6b8-eff5a3a4baf9 · outbound

This paper cites Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.676617Z

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=arxiv_source observed=2026-08-15T21:34:57.738354Z digest=sha256:5c8ecb6090579d9aa19b3cf684e0bd48f25c45bc6baac7924ec1e8839460ac5b

Observation dcfeb408-9e4c-4b96-bda5-b5a58c24a385 · outbound

This paper cites Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.659172Z

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=arxiv_source observed=2026-08-15T21:34:57.743651Z digest=sha256:656093624ba58d40301ddb0dd8a7d77012aa9ac546f4d61d87e395d1ff0835f8

Observation 42d92cef-2197-434d-a2c3-52a46530dc9e · outbound

This paper cites Generative Flows with Invertible Attentions.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Generative Flows with Invertible Attentions

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:34:57.908988Z

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=arxiv_source observed=2026-08-15T21:34:57.748511Z digest=sha256:330ec5fbd58835e8e6920849878fc5f174193084ec4668f745988ee79a502fb4

Observation d19084bf-3107-40c8-b9fb-1d3e189ffb65 · outbound

This paper cites Deep probabilistic imaging: U ncertainty quantification and multi-modal solution characterization for computational imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Deep probabilistic imaging: U ncertainty quantification and multi-modal solution characterization for computational imaging

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.640364Z

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=arxiv_source observed=2026-08-15T21:34:57.753682Z digest=sha256:3af172b0f9c8e7121b7f869f323d66c3f9703660b63719ae80e323f358a815a5

Observation 9d283c02-2e72-4be4-83aa-ad3935a42b32 · outbound

This paper cites Webster Stayman, and Jeremias Sulam.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Webster Stayman, and Jeremias Sulam

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.619946Z

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=arxiv_source observed=2026-08-15T21:34:57.759048Z digest=sha256:1b9fb5a2baabd6c155a8898c36c651ef352745931c783877c462fccd7436f6b1

Observation 80a0c07a-fb61-4a42-afa6-c640cd884b4b · outbound

This paper cites Conformal prediction under covariate shift.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Conformal prediction under covariate shift

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.597826Z

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=arxiv_source observed=2026-08-15T21:34:57.763781Z digest=sha256:5b5440ebf1a8ad2616b4789d90ea829c571be5c25940b403907c013597447e70

Observation 64fab909-0fe9-4874-b32a-961c1862edfd · outbound

This paper cites Hallucination index: A n image quality metric for generative reconstruction models.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Hallucination index: A n image quality metric for generative reconstruction models

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.579304Z

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=arxiv_source observed=2026-08-15T21:34:57.768565Z digest=sha256:d8f0c66b05fa80d6a48bda2b751f57d7861cfe91b70760939c3cb5e55369564b

Observation 7f83a1b0-8712-4011-8a3c-cfe8d1c673b5 · outbound

This paper cites Variational inference for computational imaging inverse problems.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Variational inference for computational imaging inverse problems

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.559480Z

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=arxiv_source observed=2026-08-15T21:34:57.773742Z digest=sha256:09dcf0ca35bbfaa6a92bb51a1ad3c8e7eb6e179ae688f65fd15fee91ef3cdcee

Observation 036db317-8800-4db9-b625-2ad5ac151e46 · outbound

This paper cites Algorithmic Learning in a Random World.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Algorithmic Learning in a Random World

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.538343Z

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=arxiv_source observed=2026-08-15T21:34:57.779215Z digest=sha256:5babfe6ce43322b9ca070eaa90f7482fb2e9a4ba5376cc0e7e81d7e383d376d5

Observation f9a49e5d-3af0-45e3-b55c-24dab71d3126 · outbound

This paper cites Applications of objective image quality assessment methods.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Applications of objective image quality assessment methods

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.520248Z

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=arxiv_source observed=2026-08-15T21:34:57.784268Z digest=sha256:e7179e92feb6bcc6c400aa80c7ed6c5b6ad26fc50bfaaf7858936fd48a6bd180

Observation 958b6f0e-8bb3-423b-aa33-6f7e1fdc1584 · outbound

This paper cites Image quality assessment: F rom error visibility to structural similarity.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Image quality assessment: F rom error visibility to structural similarity

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.503490Z

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=arxiv_source observed=2026-08-15T21:34:57.788973Z digest=sha256:c1186c77ae0f28d83a55118159972c1cc908f2d4afca4fa4dbea35490cb384c8

Observation 30aef41d-a9a0-4cb6-81d0-3e179824e17a · outbound

This paper cites A conditional normalizing flow for accelerated multi-coil MR imaging.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems A conditional normalizing flow for accelerated multi-coil MR imaging

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.486660Z

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=arxiv_source observed=2026-08-15T21:34:57.794022Z digest=sha256:c5eb616151f978273028078a711b8058aab73d00a7e931af0578e8d490e07664

Observation 310a87af-9867-4357-bf48-fb4b9541dd17 · outbound

This paper cites MRI CNF , 2023 b.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems MRI CNF , 2023 b

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:34:58.469542Z

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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This paper cites Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction

Reference 72

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This paper cites Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors

Reference 73

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This paper cites Reliable deep-learning-based phase imaging with uncertainty quantification.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Reliable deep-learning-based phase imaging with uncertainty quantification

Reference 74

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This paper cites Using goal-driven deep learning models to understand sensory cortex.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Using goal-driven deep learning models to understand sensory cortex

Reference 75

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Observation 731cbfc2-9300-43b0-b576-100bafb1287c · outbound

This paper cites Stable deep MRI reconstruction using generative priors.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Stable deep MRI reconstruction using generative priors

Reference 76

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Observation c22ef285-0a8c-4755-8d98-f2e50d215214 · outbound

This paper cites fastMRI: An Open Dataset and Benchmarks for Accelerated MRI.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

Reference 77

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Observation fed2c854-fb7f-463a-8937-c7ff4acf5e2e · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems The unreasonable effectiveness of deep features as a perceptual metric

Reference 78

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This paper cites write newline.

Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems write newline

Reference 79

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Pith citing papers

Observation 03faaefa-7cc0-4ecf-8197-6d80440c6313 · inbound

Flow-Based Conformal Predictive Distributions cites this paper.

Flow-Based Conformal Predictive Distributions Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems

Reference 45

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