Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent optimization provably fail to converge to global minimizers in the training of deep neural networks with ReLU activation
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.10533.
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 2026-08-16T06:04:09.675097Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T14:10:55.748563Z
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 7d58f89a-2b2c-4fde-92c0-aca6e4701d44 · inbound
Mathematical analysis of the gradients in deep learning cites this paper.
Mathematical analysis of the gradients in deep learning Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent optimization provably fail to converge to global minimizers in the training of deep neural networks with ReLU activation
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T14:10:55.752584Z
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 4838e261-417c-4152-be2f-a0ab65616662 · inbound
Sharp higher order convergence rates for the Adam optimizer cites this paper.
Sharp higher order convergence rates for the Adam optimizer Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent optimization provably fail to converge to global minimizers in the training of deep neural networks with ReLU activation
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T06:04:09.675097Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9ff34c5-c8c5-4d4b-8996-47251815b10f · inbound
Landscape analysis for shallow neural networks: Complete classification of critical points for cubic activation and affine target functions cites this paper.
Landscape analysis for shallow neural networks: Complete classification of critical points for cubic activation and affine target functions Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent optimization provably fail to converge to global minimizers in the training of deep neural networks with ReLU activation
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T00:02:19.592530Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.