Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1805.07557.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T09:18:31.526770Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T09:23:16.429548Z
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 77bd19fb-3656-45eb-b8c7-6914c9b0fafa · inbound
Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics cites this paper.
Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate
Reference 206
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T10:24:20.361099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b09b551a-c39e-4d2f-9068-243699bc102e · inbound
A Theoretical and Experimental Study of a Novel Adaptive Learning Algorithm cites this paper.
A Theoretical and Experimental Study of a Novel Adaptive Learning Algorithm Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T09:23:16.431092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.