Paper Citation Record · LEDGER

Neural Importance Sampling

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1808.03856.

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

pith.paper-citation-record.v1
1808.03856 v5

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:05:22.671242Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:58:04.199240Z

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 b6b45c2f-4c8e-4800-8619-01747012ee8d · inbound

Denoising Milky Way stellar survey data with normalizing flow models cites this paper.

Denoising Milky Way stellar survey data with normalizing flow models Neural Importance Sampling

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:05:22.671242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab8e33a1-dc20-4f03-a50d-bc0126656de0 · inbound

Monte Carlo Event Generation with Continuous Normalizing Flows cites this paper.

Monte Carlo Event Generation with Continuous Normalizing Flows Neural Importance Sampling

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:58:04.200526Z

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.

Observation e5d235b9-81f4-4b0a-9909-dc75943f87f8 · inbound

It Just Takes Two: Scaling Amortized Inference to Large Sets cites this paper.

It Just Takes Two: Scaling Amortized Inference to Large Sets Neural Importance Sampling

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T02:25:54.857595Z

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.

Observation cc4a7885-a6c3-474c-9878-ea58d793d149 · inbound

Flow-Based Surrogates for High-Dimensional Likelihoods in Experimental Neutrino Physics cites this paper.

Flow-Based Surrogates for High-Dimensional Likelihoods in Experimental Neutrino Physics Neural Importance Sampling

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-12T02:13:50.235522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 418a4800-f8f6-4435-8445-2bc261ff5e7d · inbound

Flow-Based Surrogates for High-Dimensional Likelihoods in Experimental Neutrino Physics cites this paper.

Flow-Based Surrogates for High-Dimensional Likelihoods in Experimental Neutrino Physics Neural Importance Sampling

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-13T07:05:05.761630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.