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Paper Citation Record · LEDGER

Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.07929.

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

pith.paper-citation-record.v1
2412.07929 v1

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 2026-08-07T11:48:58.581429Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:26:03.414870Z

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 0c37fb79-f8f8-4024-b00f-6cf033ad09e5 · inbound

A Budgeted Multi-Level Monte Carlo Method for Full Field Estimates of Multi-PDE Problems cites this paper.

A Budgeted Multi-Level Monte Carlo Method for Full Field Estimates of Multi-PDE Problems Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T11:48:58.581429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:48:58.581429Z digest=sha256:13da9785cea4d53c345c713e7afa3210a059ca8d21469a004e3700ab8af343b4

Observation 6b86e101-cd62-446e-843a-793927eeb41d · inbound

Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty cites this paper.

Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:26:03.554210Z

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=pdf_text observed=2026-08-07T11:25:58.785808Z digest=sha256:4582e35c1f936bab333131e5ef0d74575927da54091d7f79339d8e6acf8c501d