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Paper Citation Record · LEDGER

Machine Learning Uncertainties with Adversarial Neural Networks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1807.08763.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1807.08763 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:28:03.752219Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-09T04:47:06.055901Z

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 ee1f1083-ce54-4c9d-bfbc-df5adcbb55a5 · inbound

Looking inside jets: an introduction to jet substructure and boosted-object phenomenology cites this paper.

Looking inside jets: an introduction to jet substructure and boosted-object phenomenology Machine Learning Uncertainties with Adversarial Neural Networks

Reference 260

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:21:28.433528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-09T04:47:05.178859Z digest=sha256:636026e857fb6696b91d0ab1b97893366cfaffa542d0fa85e20839819521cfde

Observation 3b025ed0-aa27-4119-92df-b93be0109f90 · inbound

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties cites this paper.

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties Machine Learning Uncertainties with Adversarial Neural Networks

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-05T13:28:03.752219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:28:03.752219Z digest=sha256:7027136f16c1553257a525bc1429df34cdbe92bc8f6ea31d99c503e3a0c0aa0b