Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1805.06350.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-24T16:50:13.269637Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-24T16:54:42.909087Z
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 9f065a84-0f61-4f89-bd9b-ca6fbc6ef093 · inbound
Next-generation Wireless Solutions for the Smart Factory, Smart Vehicles, the Smart Grid and Smart Cities cites this paper.
Next-generation Wireless Solutions for the Smart Factory, Smart Vehicles, the Smart Grid and Smart Cities Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Reference 199
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T16:54:42.912065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.