Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Compressed Learning: A Deep Neural Network Approach
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1610.09615.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:19:52.058220Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-02T19:47:19.361474Z
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 4bb8279b-9384-4299-8c96-e6854e82b4a1 · inbound
Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging cites this paper.
Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed Learning: A Deep Neural Network Approach
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:09:15.610759Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 499f8666-e4f1-4764-a416-dc4f9321d232 · inbound
Optimized Sampling of Angle-Resolved Scatterometry Data Using End-to-End Compressed Learning Model for Nanograss Deficiency Detection cites this paper.
Optimized Sampling of Angle-Resolved Scatterometry Data Using End-to-End Compressed Learning Model for Nanograss Deficiency Detection Compressed Learning: A Deep Neural Network Approach
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T19:47:19.363071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ee99dba3-bedf-44b4-a4cf-b339f8f309a0 · inbound
Learning the Mathematical Property for Designing Low Mutual Coherence Binary Sensing Matrices cites this paper.
Learning the Mathematical Property for Designing Low Mutual Coherence Binary Sensing Matrices Compressed Learning: A Deep Neural Network Approach
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:19:52.058220Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.