Paper Citation Record · LEDGER

Probabilistic Bayesian optimal experimental design using conditional normalizing flows

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.18337.

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

pith.paper-citation-record.v1
2402.18337 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:52:16.998160Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T23:13:36.388122Z

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 6eeabdda-d082-4d2f-905b-0142bb8322a2 · inbound

Optimal experimental design: Formulations and computations cites this paper.

Optimal experimental design: Formulations and computations Probabilistic Bayesian optimal experimental design using conditional normalizing flows

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:13:36.391195Z

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.

Observation dead04df-9a86-456a-9e1d-13cd8d90ff53 · inbound

Local sensitivity-preserving random data down-sampling for experimental design cites this paper.

Local sensitivity-preserving random data down-sampling for experimental design Probabilistic Bayesian optimal experimental design using conditional normalizing flows

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:05:48.917435Z

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.

Observation d74f47b0-b00f-4e68-88d9-0a01a0485c67 · inbound

Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design cites this paper.

Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design Probabilistic Bayesian optimal experimental design using conditional normalizing flows

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T23:52:16.998160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74b2f3ca-a9d6-4e4d-94e3-f5a690dd433e · inbound

Accelerated Bayesian Optimal Experimental Design via Conditional Density Estimation and Informative Data cites this paper.

Accelerated Bayesian Optimal Experimental Design via Conditional Density Estimation and Informative Data Probabilistic Bayesian optimal experimental design using conditional normalizing flows

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:50.062098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.