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Paper Citation Record · LEDGER

Generative imaging for radio interferometry with fast uncertainty quantification

As of 10 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2507.21270.

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

pith.paper-citation-record.v1
2507.21270 v1

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measured 60 of 60 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

60 of 60 outbound references displayed

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External citation measurements

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Outbound references

Observation 0d023438-539d-41ba-921a-38d0f61e7f5d · outbound

This paper cites A., ed., , Data-Driven Models in Inverse Problems.

Generative imaging for radio interferometry with fast uncertainty quantification A., ed., , Data-Driven Models in Inverse Problems

Reference 1

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This paper cites S., Dabbech A., Wiaux Y., 2024, @doi [The Astrophysical Journal Supplement Series] 10.3847/1538-4365/ad46f5 , 273, 3.

Generative imaging for radio interferometry with fast uncertainty quantification S., Dabbech A., Wiaux Y., 2024, @doi [The Astrophysical Journal Supplement Series] 10.3847/1538-4365/ad46f5 , 273, 3

Reference 2

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This paper cites Thesis , University College London.

Generative imaging for radio interferometry with fast uncertainty quantification Thesis , University College London

Reference 3

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Observation 7369c71b-69e5-407a-826c-ce36d68ad466 · outbound

This paper cites Guided Image Generation with Conditional Invertible Neural Networks.

Generative imaging for radio interferometry with fast uncertainty quantification Guided Image Generation with Conditional Invertible Neural Networks

Reference 4

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Observation 66e3cf0b-4e7b-47ee-9021-ce6888daed6a · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 5

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Observation f823765e-292f-4f8a-99ff-1e51c54ec719 · outbound

This paper cites PMLR, pp 214--223.

Generative imaging for radio interferometry with fast uncertainty quantification PMLR, pp 214--223

Reference 6

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Observation c2a43271-1d91-4695-a34b-4c0e306629af · outbound

This paper cites A., 2018, in 2018 26th European Signal Processing Conference ( EUSIPCO ).

Generative imaging for radio interferometry with fast uncertainty quantification A., 2018, in 2018 26th European Signal Processing Conference ( EUSIPCO )

Reference 7

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Observation 606160d1-6f2c-4ba5-aea2-f8a9ec60c598 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 8

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Observation e193d9cf-ac5d-484d-aa93-f568016b3aa2 · outbound

This paper cites J., 2004, @doi [Astronomy & Astrophysics] 10.1051/0004-6361:20040354 , 426, 747.

Generative imaging for radio interferometry with fast uncertainty quantification J., 2004, @doi [Astronomy & Astrophysics] 10.1051/0004-6361:20040354 , 426, 747

Reference 9

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Observation 4e735ac5-5b79-462e-a959-e7bdc7f33f7d · outbound

This paper cites J., Golap K., Uson J.

Generative imaging for radio interferometry with fast uncertainty quantification J., Golap K., Uson J

Reference 10

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Observation 5fb6f03d-0582-45db-b4fe-3c2bc8439d6f · outbound

This paper cites L., 1998, in Advanced Technology MMW , Radio , and Terahertz Telescopes.

Generative imaging for radio interferometry with fast uncertainty quantification L., 1998, in Advanced Technology MMW , Radio , and Terahertz Telescopes

Reference 11

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This paper cites D., 2018a, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2004 , 480, 4154.

Generative imaging for radio interferometry with fast uncertainty quantification D., 2018a, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2004 , 480, 4154

Reference 12

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This paper cites D., 2018b, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2015 , 480, 4170.

Generative imaging for radio interferometry with fast uncertainty quantification D., 2018b, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2015 , 480, 4170

Reference 13

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This paper cites E., McEwen J.

Generative imaging for radio interferometry with fast uncertainty quantification E., McEwen J

Reference 14

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Generative imaging for radio interferometry with fast uncertainty quantification E., McEwen J

Reference 15

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Observation 38d0812f-1143-40e0-80ab-639a8fbe9b4e · outbound

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

Generative imaging for radio interferometry with fast uncertainty quantification Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry

Reference 16

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This paper cites L., Ravi V., Hallinan G., 2022, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stac1329 , 514, 2614.

Generative imaging for radio interferometry with fast uncertainty quantification L., Ravi V., Hallinan G., 2022, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stac1329 , 514, 2614

Reference 17

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Observation 18b4cf5d-f6d7-4258-be92-f1834af5a766 · outbound

This paper cites CLEANing Cygnus A deep and fast with R2D2.

Generative imaging for radio interferometry with fast uncertainty quantification CLEANing Cygnus A deep and fast with R2D2

Reference 18

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 19

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Observation a620aee4-b5c1-4ef8-89d2-314fea983b25 · outbound

This paper cites IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors.

Generative imaging for radio interferometry with fast uncertainty quantification IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors

Reference 20

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 21

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This paper cites Society of Exploration Geophysicists, pp 1135--1138, @doi 10.1190/1.1885591.

Generative imaging for radio interferometry with fast uncertainty quantification Society of Exploration Geophysicists, pp 1135--1138, @doi 10.1190/1.1885591

Reference 22

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Observation dd59b27f-b0a1-4762-856b-00428819adcd · outbound

This paper cites Generative Adversarial Networks.

Generative imaging for radio interferometry with fast uncertainty quantification Generative Adversarial Networks

Reference 26

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Observation 13b0e513-09eb-4c72-94e7-31207078617f · outbound

This paper cites fastRESOLVE: fast Bayesian imaging for aperture synthesis in radio astronomy.

Generative imaging for radio interferometry with fast uncertainty quantification fastRESOLVE: fast Bayesian imaging for aperture synthesis in radio astronomy

Reference 27

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Generative imaging for radio interferometry with fast uncertainty quantification C., 2017, in Advances in Neural Information Processing Systems

Reference 28

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 29

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This paper cites A., 1974, Astronomy and Astrophysics, https://ui.adsabs.harvard.edu/abs/1974A&AS...15..417H 15, 55.

Generative imaging for radio interferometry with fast uncertainty quantification A., 1974, Astronomy and Astrophysics, https://ui.adsabs.harvard.edu/abs/1974A&AS...15..417H 15, 55

Reference 30

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This paper cites A., 2017, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.

Generative imaging for radio interferometry with fast uncertainty quantification A., 2017, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

Reference 31

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Observation a87daf6a-564c-437c-84e0-e0cfd309a00f · outbound

This paper cites R., Selig M., En lin T.

Generative imaging for radio interferometry with fast uncertainty quantification R., Selig M., En lin T

Reference 32

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Generative imaging for radio interferometry with fast uncertainty quantification Metric Gaussian Variational Inference

Reference 33

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Generative imaging for radio interferometry with fast uncertainty quantification PMLR, pp 19256--19273

Reference 34

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Generative imaging for radio interferometry with fast uncertainty quantification I., Mars M., Price M

Reference 35

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Observation ba4096b4-c72b-44f2-b861-278226b38ecc · outbound

This paper cites M., McEwen J.

Generative imaging for radio interferometry with fast uncertainty quantification M., McEwen J

Reference 36

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Observation ba7cbf2b-5c34-4227-9a37-f62417ec6da4 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification M., McEwen J

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Generative imaging for radio interferometry with fast uncertainty quantification R., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1368 , 444, 606

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Observation fa2f1f4e-86f0-48de-8b80-3d05c4f09456 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification D., d'Avezac M., Carrillo R

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Observation d13ceb0b-1355-4bc4-a1ae-faad932dd691 · outbound

This paper cites Distributed and parallel sparse convex optimization for radio interferometry with PURIFY.

Generative imaging for radio interferometry with fast uncertainty quantification Distributed and parallel sparse convex optimization for radio interferometry with PURIFY

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Observation 2e8ef2bd-f2a3-49ae-83c9-259874efd2dc · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification M., Frangi A

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Observation 94471bfd-91bd-4526-910e-efee56d8b97a · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification M., 2011, @doi [Astronomy & Astrophysics] 10.1051/0004-6361/201116434 , 527, A107

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Observation 454960b5-4250-45a3-8794-815914850848 · outbound

This paper cites Curran Associates, Inc.

Generative imaging for radio interferometry with fast uncertainty quantification Curran Associates, Inc

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Observation 052f6004-2696-4e3b-a38f-8d482aedcb80 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification M., Fenech D

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Observation 5b8a655c-7619-44db-ba26-40a4820a8e95 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification L., 2021, @doi [Proceedings of the AAAI Conference on Artificial Intelligence] 10.1609/aaai.v35i3.16366 , 35, 2628

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Observation 33fc614f-70ab-4b0d-b6b7-2eb28b582433 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification M., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stt2244 , 438, 768

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Generative imaging for radio interferometry with fast uncertainty quantification C., et al., 2022, @doi [Publications of the Astronomical Society of the Pacific] 10.1088/1538-3873/ac9642 , 134, 114501

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Observation a66b1207-15e3-49bc-8e0e-b5787c442842 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Observation 6f9c8988-f545-4787-a74a-0e56c6280403 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Observation 013dde4b-a763-4804-b9a8-bc9418abf6b7 · outbound

This paper cites The AIRI plug-and-play algorithm for image reconstruction in radio-interferometry: variations and robustness.

Generative imaging for radio interferometry with fast uncertainty quantification The AIRI plug-and-play algorithm for image reconstruction in radio-interferometry: variations and robustness

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Observation 91c90b3e-8f38-48ee-92ac-1b67b24c4498 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification R., Moran J

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Observation c9ded39d-89fe-4b01-8ccd-89d9f223dd75 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

Reference 54

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Observation f000081b-45a5-471d-9561-8074cf143c00 · outbound

This paper cites IOS Press, pp 2499--2506, @doi 10.3233/FAIA230554.

Generative imaging for radio interferometry with fast uncertainty quantification IOS Press, pp 2499--2506, @doi 10.3233/FAIA230554

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Source-reported events for the cited work

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Observation d105e1d7-0757-4900-84c3-b1ea7549814b · outbound

This paper cites Using conditional GANs for convergence map reconstruction with uncertainties.

Generative imaging for radio interferometry with fast uncertainty quantification Using conditional GANs for convergence map reconstruction with uncertainties

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Observation a362c9fa-e9c0-4fef-8f12-cfda32646818 · outbound

This paper cites J., Liaudat T.

Generative imaging for radio interferometry with fast uncertainty quantification J., Liaudat T

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Source-reported events for the cited work

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Observation 9c6b8025-1ae7-4f0b-9f4d-fc5da29ab520 · outbound

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Generative imaging for radio interferometry with fast uncertainty quantification Learning Likelihoods with Conditional Normalizing Flows

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b8f6f234-1a1b-4378-8ba9-9600f5f0c062 · outbound

This paper cites an unresolved cited work.

Generative imaging for radio interferometry with fast uncertainty quantification Unresolved cited work

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Source-reported events for the cited work

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Observation 51d8c20e-4566-4698-bee8-1be090b5c570 · outbound

This paper cites I.-C., Xu Y., 2021, in International Conference on Learning Representations.

Generative imaging for radio interferometry with fast uncertainty quantification I.-C., Xu Y., 2021, in International Conference on Learning Representations

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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.

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Pith citing papers

No inbound Pith citation observations are available.