Paper Citation Record · LEDGER

Recurrent Inference Machines for Solving Inverse Problems

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1706.04008.

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

pith.paper-citation-record.v1
1706.04008 v1

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 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:31:20.798480Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

95
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e8c23945-ab0c-43cd-aa42-c889be640e65 · inbound

Learning to See: Applying Inverse Recurrent Inference Machines to See through Refractive Scattering cites this paper.

Learning to See: Applying Inverse Recurrent Inference Machines to See through Refractive Scattering Recurrent Inference Machines for Solving Inverse Problems

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T15:31:20.798480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Data-driven approaches to inverse problems cites this paper.

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 e8ff573a-15d9-48f3-aa7b-1f1993fdaa52 · inbound

Learned iterative networks: An operator learning perspective cites this paper.

Learned iterative networks: An operator learning perspective Recurrent Inference Machines for Solving Inverse Problems

Reference 121

Resolution: unresolved; no resolver link, observed 2026-08-03T17:44:53.117573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9397f52c-3378-47a1-9e46-abfc2b8d75e2 · inbound

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines cites this paper.

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines Recurrent Inference Machines for Solving Inverse Problems

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-01T12:49:49.482971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.