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Paper Citation Record · LEDGER

BayesFlow: Amortized Bayesian Workflows With Neural Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.16015.

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

pith.paper-citation-record.v1
2306.16015 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:58:04.063727Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T20:58:04.262824Z

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 b7aeefbf-203b-4b0b-afbc-ee8b6313afd3 · inbound

Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation cites this paper.

Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation BayesFlow: Amortized Bayesian Workflows With Neural Networks

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-08-08T20:58:04.266542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-08T20:58:04.063727Z digest=sha256:ffeda9957ced047cd7157c641e66397eb93cef284f9701e8bf0cee38b6fd9e3f

Observation abe2f147-b197-482f-b4a5-ecebee33c1e1 · inbound

AIM: Amortized Inference for Multistate Transition Models cites this paper.

AIM: Amortized Inference for Multistate Transition Models BayesFlow: Amortized Bayesian Workflows With Neural Networks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-31T23:55:56.695754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:55:56.695754Z digest=sha256:948a8553260e5f85d140a9fc8bbaa31c80232ea1b69014e64ac293c8020f739a