Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the existence of global minima and convergence analyses for gradient descent methods in the training of deep neural networks
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2112.09684.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:10:55.187721Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T14:10:55.689224Z
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 56865051-e276-4cac-8445-25a6fb17bf8d · inbound
Mathematical analysis of the gradients in deep learning cites this paper.
Mathematical analysis of the gradients in deep learning On the existence of global minima and convergence analyses for gradient descent methods in the training of deep neural networks
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T14:10:55.693711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.