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Paper Citation Record · LEDGER

A theory of data variability in Neural Network Bayesian inference

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.16695.

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

pith.paper-citation-record.v1
2307.16695 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:36:55.506896Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T07:27:09.068375Z

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 56875dc2-751c-4c71-a994-2cb0ea39878d · inbound

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning cites this paper.

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning A theory of data variability in Neural Network Bayesian inference

Reference 1991

Resolution
unresolved
no resolver link, observed 2026-08-09T05:36:55.506896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:36:55.506896Z digest=sha256:e0dc1ec74d2e484f5c5fce1d44cc031c17ff2fd7258de005a0d19897c899bba8

Observation 57def729-fcfe-4fb2-b001-f8ec6c3a3307 · inbound

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning cites this paper.

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning A theory of data variability in Neural Network Bayesian inference

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-05-19T07:27:09.069954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T07:25:02.419951Z digest=sha256:8dbc9ed4be2f5bbe0ec6f99e73868e90492afd322388f56599530c47820bec8d