Paper Citation Record · LEDGER

Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.01052.

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

pith.paper-citation-record.v1
2402.01052 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:44:21.445020Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:35:53.945259Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 dff95f9e-3b85-4e56-920d-045f306a481c · inbound

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

Benchmarking learned algorithms for computed tomography image reconstruction tasks Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T17:57:56.178441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6662ef6-3fc4-4efd-95c2-cbb10179af32 · 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 Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T05:15:53.224530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c5af011-e6a7-4566-8515-f2339fad6e6f · inbound

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise cites this paper.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T21:44:21.445020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96d485fc-fc7d-4a44-9385-7868b56fcb88 · inbound

Weakly-Convex Regularization for Magnetic Resonance Image Denoising cites this paper.

Weakly-Convex Regularization for Magnetic Resonance Image Denoising Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-05T18:35:54.023222Z

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.