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Paper Citation Record · LEDGER

Learned convex regularizers for inverse problems

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2008.02839.

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

pith.paper-citation-record.v1
2008.02839 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:44:40.418553Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:30:29.018707Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a2767d26-d693-49f8-b3a0-fd46abb89bf0 · inbound

Augmented NETT Regularization of Inverse Problems cites this paper.

Augmented NETT Regularization of Inverse Problems Learned convex regularizers for inverse problems

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-14T14:36:00.620319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:36:00.620319Z digest=sha256:7b4501fed1fae891e25163e7976404a26fbf81e5626fd2c1c51f41c96f4133fe

Observation e42131d6-f0ab-4c7e-9552-1eda98d2a856 · inbound

An Adaptively Inexact Method for Bilevel Learning Using Primal-Dual Style Differentiation cites this paper.

An Adaptively Inexact Method for Bilevel Learning Using Primal-Dual Style Differentiation Learned convex regularizers for inverse problems

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T19:45:26.480429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:45:26.480429Z digest=sha256:5da8434619ae6132097884b56f64ba79aa2c1e7ee660be0e24304423b878b4e3

Observation 38c8d2b4-06f8-4d8f-aaea-3900f8e1aef9 · inbound

Benchmarking learned algorithms for computed tomography image reconstruction tasks cites this paper.

Benchmarking learned algorithms for computed tomography image reconstruction tasks Learned convex regularizers for inverse problems

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-11T17:57:56.371771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:57:56.371771Z digest=sha256:e3cc955114146fe06359ccfc854416317e3029f34b6cb4fabc3cf981155b8b3c

Observation 8de62096-67a7-4608-b1db-b00b35c03775 · inbound

MAP Image Recovery with Guarantees using Locally Convex Multi-Scale Energy (LC-MUSE) Model cites this paper.

MAP Image Recovery with Guarantees using Locally Convex Multi-Scale Energy (LC-MUSE) Model Learned convex regularizers for inverse problems

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T05:15:53.210625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:15:53.210625Z digest=sha256:ed3787c3af29e902ff1604621c568136e83215ee681d456f661a7b2d811d5c21

Observation 5f3367df-a424-43ab-8f3f-f059f8635dc9 · inbound

Good Things Come in Pairs: Paired Autoencoders for Inverse Problems cites this paper.

Good Things Come in Pairs: Paired Autoencoders for Inverse Problems Learned convex regularizers for inverse problems

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-15T22:44:40.418553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:44:40.418553Z digest=sha256:052b9f92baa7608657d046ecafd3b109126033caedd29f7f1711f62f6f5ae84f

Observation 03c82f30-cb76-482a-baad-b8e9b79b4964 · inbound

Nonlinear Joint Spectral Radius cites this paper.

Nonlinear Joint Spectral Radius Learned convex regularizers for inverse problems

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:30:29.025205Z

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=pdf_text observed=2026-08-06T17:30:27.795841Z digest=sha256:7346afd25d2d66ea50e27b983ec78bba55e4838208115f49c7ff144d10a389a4