Paper Citation Record · LEDGER

Adam with model exponential moving average is effective for nonconvex optimization

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.18199.

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

pith.paper-citation-record.v1
2405.18199 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 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:11:05.977992Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T22:15:39.248090Z

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 e0bbf124-a42c-4a9c-a453-9ba6a7d95d29 · inbound

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems cites this paper.

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems Adam with model exponential moving average is effective for nonconvex optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T21:11:05.977992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ede2bde-50d0-4e6b-b914-b26768d3a5f4 · 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 Adam with model exponential moving average is effective for nonconvex optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:44.027164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 730f562c-a0f9-43a8-b423-de0fad824a76 · inbound

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

Central limit theorem for the averaged Adam optimizer Adam with model exponential moving average is effective for nonconvex optimization

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:29:38.394340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27815649-896f-4921-98df-e2e0bb6bb6ae · inbound

Differentially Private Natural Gradient Descent cites this paper.

Differentially Private Natural Gradient Descent Adam with model exponential moving average is effective for nonconvex optimization

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-08T22:15:39.249435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 575ef6ac-2535-4f35-9d03-fddd2e122113 · inbound

The Convergence Behavior of Adam under Heavy-Tailed Noise cites this paper.

The Convergence Behavior of Adam under Heavy-Tailed Noise Adam with model exponential moving average is effective for nonconvex optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T08:37:46.169366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 057fc1c3-65aa-48c1-b948-718d23632291 · inbound

The Convergence Behavior of Adam under Heavy-Tailed Noise cites this paper.

The Convergence Behavior of Adam under Heavy-Tailed Noise Adam with model exponential moving average is effective for nonconvex optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T03:30:54.186249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.