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Paper Citation Record · LEDGER

Variational methods for simulation-based inference

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.04176.

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

pith.paper-citation-record.v1
2203.04176 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:58:04.003451Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T20:58:04.329081Z

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 7d603334-0521-4774-8b03-353b6da4459f · 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 Variational methods for simulation-based inference

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-08T20:58:04.332175Z

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=arxiv_source observed=2026-08-08T20:58:04.003451Z digest=sha256:05fddd113d2883a78bcb8c2a9bcc3a6437ff516227ce053b6d4fc315dc09dd37

Observation eb1720ce-cf15-4506-ae10-b74acbab1016 · inbound

A Hierarchical Validity-Audit Framework for Neural Mass Models in Simulation-Based Inference: From Observational Coverage to Mechanistic Interpretation cites this paper.

A Hierarchical Validity-Audit Framework for Neural Mass Models in Simulation-Based Inference: From Observational Coverage to Mechanistic Interpretation Variational methods for simulation-based inference

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-31T23:13:16.895930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:13:16.895930Z digest=sha256:08e3d5f1a11848bf669121dcf47f81802a18eec306cf727aa851b08095a64aac