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Paper Citation Record · LEDGER

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.04465.

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

pith.paper-citation-record.v1
2311.04465 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:44:49.460969Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T11:44:50.596139Z

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 b2b3c031-7557-42a3-8774-bc6e89bd561d · inbound

LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process cites this paper.

LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:44:50.693445Z

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=2026-08-06T11:44:49.460969Z digest=sha256:e86eb6433add3b5a24ac88fb3c6970b1b6865bb71dc4bca1b13a13a8d8efbc60

Observation 306919f2-3b77-47fd-bb4d-5e28d1ab6935 · inbound

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications cites this paper.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T00:38:16.329921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:38:16.329921Z digest=sha256:84d58011df078031979cd3b19ad31e0214c442c3ba083feed0046dc16607c4f2