Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Learning in Neural Networks: An Overview
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1404.7828.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T14:04:22.969690Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-19T04:37:04.126189Z
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 9ac58459-332d-4910-a3fd-a9ee9f3fd893 · inbound
Attentive Deep Regression Networks for Real-Time Visual Face Tracking in Video Surveillance cites this paper.
Attentive Deep Regression Networks for Real-Time Visual Face Tracking in Video Surveillance Deep Learning in Neural Networks: An Overview
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T14:04:22.969690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d76816c2-93a3-40a1-a6d0-bd66929cd8b5 · inbound
A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component cites this paper.
A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Deep Learning in Neural Networks: An Overview
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:12:33.506989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76e4d4dc-0999-4b0a-891f-86a8160d20ad · inbound
Implementing An Artificial Quantum Perceptron cites this paper.
Implementing An Artificial Quantum Perceptron Deep Learning in Neural Networks: An Overview
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:57:26.945574Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1aa8594-8366-4aca-94b9-1ee1af4c3278 · inbound
Reproducibility of machine learning analyses of 21 cm reionization maps cites this paper.
Reproducibility of machine learning analyses of 21 cm reionization maps Deep Learning in Neural Networks: An Overview
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:05:34.317605Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a480a893-238a-4b71-b301-b3de4044e64f · inbound
Reduced Order Models and Conditional Expectation -- Analysing Parametric Low-Order Approximations cites this paper.
Reduced Order Models and Conditional Expectation -- Analysing Parametric Low-Order Approximations Deep Learning in Neural Networks: An Overview
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T06:00:03.019332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf446a2f-7fa2-4350-9920-676484cb2676 · inbound
R-process heating implementation in hydrodynamic simulations with neural networks cites this paper.
R-process heating implementation in hydrodynamic simulations with neural networks Deep Learning in Neural Networks: An Overview
Reference 57
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-19T04:37:04.128687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4e25e7ab-722d-4424-b587-a9bf1efa8c03 · inbound
Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models cites this paper.
Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Deep Learning in Neural Networks: An Overview
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:26:37.704978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.