Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.05825.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T08:17:15.461026Z
A source-named dated measurement, never combined with another source.
Source: cited_works
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 6728cb05-bed0-42b8-871b-264f5279a3b4 · inbound
Likelihood Reconstruction for Radio Detectors of Neutrinos and Cosmic Rays cites this paper.
Likelihood Reconstruction for Radio Detectors of Neutrinos and Cosmic Rays Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:17:15.461026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbb3c372-4377-40c4-9d62-4cccdf411244 · inbound
Light Antinuclei Coalescence: Femtoscopic Constraints via Neural-Flow Surrogates cites this paper.
Light Antinuclei Coalescence: Femtoscopic Constraints via Neural-Flow Surrogates Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T07:27:39.244000Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.