Paper Citation Record · LEDGER

Convergence rates for the Adam optimizer

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.21078.

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

pith.paper-citation-record.v1
2407.21078 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 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:20:45.494765Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:29:38.395619Z

Reference resolution

0 of 0 outbound references displayed

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verified fuzzy0
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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 7561269f-221b-42ab-b3e7-386f24565866 · inbound

PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning cites this paper.

PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning Convergence rates for the Adam optimizer

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:45.494765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20c2675d-46b9-4d78-857e-23e58d6f10d4 · inbound

Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization cites this paper.

Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization Convergence rates for the Adam optimizer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-14T18:47:36.593770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8253dc68-0c89-4955-849a-615ab6ab6c6c · inbound

Central limit theorem for the averaged Adam optimizer cites this paper.

Central limit theorem for the averaged Adam optimizer Convergence rates for the Adam optimizer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:29:38.397461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7dece8a-b8f7-405f-80bf-1cd65feb3371 · inbound

Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks cites this paper.

Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks Convergence rates for the Adam optimizer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T20:46:05.467029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.