Paper Citation Record · LEDGER

Data-driven approaches to inverse problems

As of 19 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 3 inbound Pith citation observations for arXiv:2506.11732.

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

pith.paper-citation-record.v1
2506.11732 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:12.118389Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:06:48.049947Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

30 of 30 outbound references displayed

verified exact10
verified fuzzy10
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 026a986e-fd1a-44c1-891a-14e5f2880cd8 · outbound

This paper cites Gradient Step Denoiser for convergent Plug-and-Play.

Data-driven approaches to inverse problems Gradient Step Denoiser for convergent Plug-and-Play

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:09.520464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d5f7107-3b37-4ca6-9ffb-ff35c229dfd7 · outbound

This paper cites Discretization-invariant Bayesian inversion and Besov space priors.

Data-driven approaches to inverse problems Discretization-invariant Bayesian inversion and Besov space priors

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:13.481726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e312c5a-a196-42a7-a7d8-3ec3831a3d70 · outbound

This paper cites Sellars, A.

Data-driven approaches to inverse problems Sellars, A

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:15.552588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32ecd47a-9a13-47bc-b79b-e8d9c0cf9fd6 · outbound

This paper cites Shumaylov, J.

Data-driven approaches to inverse problems Shumaylov, J

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:15.382983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a6586100-e803-426f-8b1a-1b6e479c37dc · outbound

This paper cites Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance).

Data-driven approaches to inverse problems Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:11.384486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25028387-5970-402a-a45c-d4ab6030f4e6 · outbound

This paper cites Stochastic Primal-Dual Deep Unrolling.

Data-driven approaches to inverse problems Stochastic Primal-Dual Deep Unrolling

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:13.056932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36b225c9-2a85-410a-a781-7fe24613f437 · outbound

This paper cites an unresolved cited work.

Data-driven approaches to inverse problems Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:15.185146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49da3469-858f-4f75-b180-1f75d9d254f2 · outbound

This paper cites Terris, A.

Data-driven approaches to inverse problems Terris, A

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:14.982070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ddcc2e70-570e-44cb-b113-ec65c7dee0d1 · outbound

This paper cites Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling.

Data-driven approaches to inverse problems Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:12.900722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b107006-65a3-4952-94c2-d9a3544a5ae4 · outbound

This paper cites Understanding Trainable Sparse Coding via Matrix Factorization.

Data-driven approaches to inverse problems Understanding Trainable Sparse Coding via Matrix Factorization

Reference 1965

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:14.242157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38d1a7a3-fb00-4fe6-a9b7-30417c3d6a5a · outbound

This paper cites Rudzusika, B.

Data-driven approaches to inverse problems Rudzusika, B

Reference 1992

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:15.790327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a20543a7-74b0-4195-94e9-441424e73955 · outbound

This paper cites Masnou and J.-M.

Data-driven approaches to inverse problems Masnou and J.-M

Reference 1993

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:16.068709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2f89701c-e6b0-4f4f-bc2b-b89b062f6cb1 · outbound

This paper cites On the Uniqueness of Kantorovich Potentials.

Data-driven approaches to inverse problems On the Uniqueness of Kantorovich Potentials

Reference 1998

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:13.253473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9915812-d7f7-4c4f-8087-0b83f1d083e2 · outbound

This paper cites Novaga and E.

Data-driven approaches to inverse problems Novaga and E

Reference 2001

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:15.923219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87751ecf-8f0e-402b-a05d-69bab8be1c70 · outbound

This paper cites De Giorgi.

Data-driven approaches to inverse problems De Giorgi

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:16.821664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 77cd749c-73e7-4503-8e36-9fa577d53db8 · outbound

This paper cites Obmann and M.

Data-driven approaches to inverse problems Obmann and M

Reference 2005

Resolution: verified exact; raw_fallback, observed 2026-08-07T04:09:13.815051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d8e95052-c308-465b-aed9-6da599a61a8d · outbound

This paper cites Recurrent Inference Machines for Solving Inverse Problems.

Data-driven approaches to inverse problems Recurrent Inference Machines for Solving Inverse Problems

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:10.722995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bf4eaad-da4b-4454-8b31-48814a506045 · outbound

This paper cites URLhttps://doi.org/10.1137/080728548.

Data-driven approaches to inverse problems URLhttps://doi.org/10.1137/080728548

Reference 2009

Resolution: verified exact; doi, observed 2026-08-07T04:09:12.643928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3bc8b12a-9f4c-43dc-8fb5-9dc393c43eba · outbound

This paper cites Buades, B.

Data-driven approaches to inverse problems Buades, B

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:17.070429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c30670eb-f038-426e-80c3-08aa97f07285 · outbound

This paper cites an unresolved cited work.

Data-driven approaches to inverse problems Unresolved cited work

Reference 2012

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:14.801734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 252be915-378e-4df8-8ef0-f9414cfbf9e7 · outbound

This paper cites an unresolved cited work.

Data-driven approaches to inverse problems Unresolved cited work

Reference 2014

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:17.336809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 31e42b7b-4461-4190-8e04-1ea202b7a899 · outbound

This paper cites Learning convex regularizers satisfying the variational source condition for inverse problems.

Data-driven approaches to inverse problems Learning convex regularizers satisfying the variational source condition for inverse problems

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:14.068655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efb2d59b-b2a4-41d0-9f51-365e6df62ac9 · outbound

This paper cites A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications.

Data-driven approaches to inverse problems A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications

Reference 2017

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T04:09:14.469230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation daa8b2c5-82a4-42cb-98b5-dcc979c1c94c · outbound

This paper cites an unresolved cited work.

Data-driven approaches to inverse problems Unresolved cited work

Reference 2018

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:17.718995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 60593a3d-4837-4a7b-88ee-c664f36be127 · outbound

This paper cites Gilton, G.

Data-driven approaches to inverse problems Gilton, G

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:16.437638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5aee7f6-1bba-4307-989b-15aa64c0fe38 · outbound

This paper cites Driggs, J.

Data-driven approaches to inverse problems Driggs, J

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:16.628866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 711d1df0-fd92-453a-be91-50fc3cb38176 · outbound

This paper cites Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling.

Data-driven approaches to inverse problems Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling

Reference 2021

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:14.641840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bd7b539a-ced9-4ed4-bca5-e6234bc2b943 · outbound

This paper cites 2022.3207451.

Data-driven approaches to inverse problems 2022.3207451

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-07T04:09:10.349824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50848a10-6b30-4ed9-a267-b2ac37d27a1e · outbound

This paper cites an unresolved cited work.

Data-driven approaches to inverse problems Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:16.267499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c16ccd6-89c5-45d9-a901-956ad2786d06 · outbound

This paper cites URLhttps://www.aimsciences.org/article/ id/67ab0b783942fc6603063e6e.

Data-driven approaches to inverse problems URLhttps://www.aimsciences.org/article/ id/67ab0b783942fc6603063e6e

Reference 2025

Resolution: verified exact; doi, observed 2026-08-07T04:09:12.431183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation f3b184d6-3b0c-46a9-9b68-039c2d6b710d · inbound

Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error cites this paper.

Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error Data-driven approaches to inverse problems

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:22:46.986828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6ca74370-6668-46a3-8584-68dd7de03574 · inbound

PyCC.id: A package for hypothesis-driven equation discovery with structural identifiability cites this paper.

PyCC.id: A package for hypothesis-driven equation discovery with structural identifiability Data-driven approaches to inverse problems

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.278349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e72e16f3-7c21-4a13-b41c-2289db8bef5e · inbound

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions cites this paper.

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions Data-driven approaches to inverse problems

Reference 109

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T19:11:10.714730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.