Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Modelling the influence of data structure on learning in neural networks: the hidden manifold model
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1909.11500.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T13:21:59.076281Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T15:35:47.464716Z
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 42b5ccb4-cf05-45b5-ba70-a06f8da45991 · inbound
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces cites this paper.
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces Modelling the influence of data structure on learning in neural networks: the hidden manifold model
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:21:59.076281Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5aa0d47-99c8-4e66-bb2a-dcfe22ae16d8 · inbound
DNNs, Dataset Statistics, and Correlation Functions cites this paper.
DNNs, Dataset Statistics, and Correlation Functions Modelling the influence of data structure on learning in neural networks: the hidden manifold model
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T20:35:13.239374Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cae6c211-aa59-4fb0-af16-6c45b87cb4ee · inbound
Spectral phase transitions and trainability in neural network learning dynamics cites this paper.
Spectral phase transitions and trainability in neural network learning dynamics Modelling the influence of data structure on learning in neural networks: the hidden manifold model
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:35:47.466366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.