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Paper Citation Record · LEDGER

Priors in Bayesian Deep Learning: A Review

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.06868.

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

pith.paper-citation-record.v1
2105.06868 v3

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:03:56.644997Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T04:12:02.604111Z

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 6e5ecaa3-6e78-484d-a872-cf4ac309d415 · inbound

Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators cites this paper.

Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators Priors in Bayesian Deep Learning: A Review

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:12:02.606333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T04:07:42.061343Z digest=sha256:0627114d6823655ed18387908d1ec41d6a141e68cc836f684a622b883c0ff054

Observation 65b48e54-33f9-43ee-b701-81165ecda8a8 · inbound

laplax -- Laplace Approximations with JAX cites this paper.

laplax -- Laplace Approximations with JAX Priors in Bayesian Deep Learning: A Review

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T15:03:56.644997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:03:56.644997Z digest=sha256:0fa758411236096fac543e8885bfb3e31f70df7055ec7139df135e1b9af04516