Paper Citation Record · LEDGER

A Primer on Bayesian Neural Networks: Review and Debates

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2309.16314.

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

pith.paper-citation-record.v1
2309.16314 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:14:56.444483Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:29:00.690047Z

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 f8f42239-6dec-45fe-b4bd-c9b84ac22cf3 · inbound

Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials cites this paper.

Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials A Primer on Bayesian Neural Networks: Review and Debates

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-12T15:40:22.543985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 471f991d-ce85-44b2-8394-985f31873abd · inbound

Can Bayesian Neural Networks Make Confident Predictions? cites this paper.

Can Bayesian Neural Networks Make Confident Predictions? A Primer on Bayesian Neural Networks: Review and Debates

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T18:02:18.642157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21987ec0-091c-4a42-8b9e-b376672152f0 · inbound

Last-layer committee machines for uncertainty estimations of benthic imagery cites this paper.

Last-layer committee machines for uncertainty estimations of benthic imagery A Primer on Bayesian Neural Networks: Review and Debates

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:14:56.444483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9f7bc9e-abeb-4926-84c9-d115c100fa23 · inbound

Emulating compact binary population synthesis simulations with uncertainty quantification and model comparison using Bayesian normalizing flows cites this paper.

Emulating compact binary population synthesis simulations with uncertainty quantification and model comparison using Bayesian normalizing flows A Primer on Bayesian Neural Networks: Review and Debates

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:19.652116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53d4c8e9-cb92-40bb-9cb2-edd54826b21e · inbound

Last Layer Hamiltonian Monte Carlo cites this paper.

Last Layer Hamiltonian Monte Carlo A Primer on Bayesian Neural Networks: Review and Debates

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.361368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5454adf2-2216-462d-bb4a-1bfe4a24a805 · inbound

Minimaxity and Admissibility of Bayesian Neural Networks cites this paper.

Minimaxity and Admissibility of Bayesian Neural Networks A Primer on Bayesian Neural Networks: Review and Debates

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:45:50.634344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 78d16ac1-761b-4e02-8ee4-ea8771022436 · inbound

Reconstructing Galactic Gravitational Potentials from Stellar Kinematics with Physics-Informed Neural Networks cites this paper.

Reconstructing Galactic Gravitational Potentials from Stellar Kinematics with Physics-Informed Neural Networks A Primer on Bayesian Neural Networks: Review and Debates

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T22:29:00.691562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1d8c4b4-6ad6-4617-9218-c6c372d8a319 · inbound

Uncertainty quantification for trustworthy deep learning: Methods and measures cites this paper.

Uncertainty quantification for trustworthy deep learning: Methods and measures A Primer on Bayesian Neural Networks: Review and Debates

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T13:23:56.740296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.