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Paper Citation Record · LEDGER

A practical tutorial on Variational Bayes

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2103.01327.

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

pith.paper-citation-record.v1
2103.01327 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:34:29.349518Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

21
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e143cf45-52e5-4b03-9e83-6f92f80e9640 · inbound

Variational Bayes on Manifolds cites this paper.

Variational Bayes on Manifolds A practical tutorial on Variational Bayes

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T14:34:29.349518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:34:29.349518Z digest=sha256:432b8ba56b034b26597325d2caa9e6537369ce8a6a1bdfcad322e90a544931e7

Observation 24d0a541-2cd8-4be2-833e-d8d93a395f32 · inbound

Bayesian Active Learning for Bayesian Model Updating: the Art of Acquisition Functions and Beyond cites this paper.

Bayesian Active Learning for Bayesian Model Updating: the Art of Acquisition Functions and Beyond A practical tutorial on Variational Bayes

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:31:06.969116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-18T08:28:21.351602Z digest=sha256:5800f37a579cbd08262f27c988fd6e48587a72387ec3d43e90e23eb2541e3142

Observation bc69573c-6867-46e5-9857-b6889ff18315 · inbound

A Cubing Strategy for Identifying Stable Hyperparameter Regions for Uncertainty Quantification in Spatial Deep Learning cites this paper.

A Cubing Strategy for Identifying Stable Hyperparameter Regions for Uncertainty Quantification in Spatial Deep Learning A practical tutorial on Variational Bayes

Reference 101

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:17:48.588167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-19T21:14:45.344663Z digest=sha256:c2afb0c3ba538758fa5f061437489d71ac69f2ac9481e109ba08811e2ec1e5d8

Observation 0d484a33-2e5c-4de5-9f7c-10f314fab1ed · inbound

Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation cites this paper.

Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation A practical tutorial on Variational Bayes

Reference 64

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T02:14:10.131854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-30T02:12:45.635294Z digest=sha256:24472bc5b01cce87e52871f9052d927ba53982a556491711dfe65641a1c599c0

Observation c4e1bccc-b22c-40a4-9876-8143fbfde2fd · inbound

Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation cites this paper.

Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation A practical tutorial on Variational Bayes

Reference 189

Resolution
verified exact
arxiv_id, observed 2026-06-30T02:14:11.158821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-30T02:12:45.635294Z digest=sha256:df7e32f380728d0bfa97d12b26d5de48bf33cf289c62e216786ec9507df9a11e