Paper Citation Record · LEDGER

Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2211.08875.

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

pith.paper-citation-record.v1
2211.08875 v3

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 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:57:05.200565Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:52:35.021099Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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malformed identifier0
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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 15d98b8f-efa7-4bf6-9f6c-f1032f5b4186 · inbound

Contextual Online Decision Making with Infinite-Dimensional Functional Regression cites this paper.

Contextual Online Decision Making with Infinite-Dimensional Functional Regression Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 2003

Resolution: unresolved; no resolver link, observed 2026-08-09T23:57:05.200565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22f4d560-dad1-4320-bc1c-f151903d818e · inbound

Operator Learning for Schr\"{o}dinger Equation: Unitarity, Error Bounds, and Time Generalization cites this paper.

Operator Learning for Schr\"{o}dinger Equation: Unitarity, Error Bounds, and Time Generalization Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-19T13:07:18.207821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7bc0c9e4-964d-4b10-8049-05d7576e7a91 · inbound

Safety Certification is Classification cites this paper.

Safety Certification is Classification Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:56:09.230609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 548fed72-eb25-48ca-bb1c-f6dd93e968b8 · inbound

Concentration Inequalities for Sample Cross-Covariances cites this paper.

Concentration Inequalities for Sample Cross-Covariances Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 259

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:27:48.880451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ac956be4-7b27-48b2-be19-4241642ae424 · inbound

Is Zero-Shot Super-Resolution Possible in Operator Learning? cites this paper.

Is Zero-Shot Super-Resolution Possible in Operator Learning? Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:52:35.022780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 93d8fbbd-4e75-4f5a-8958-f1cb5a5beed2 · inbound

Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles cites this paper.

Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T17:37:50.754969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.