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Paper Citation Record · LEDGER

Understanding Probabilistic Sparse Gaussian Process Approximations

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1606.04820.

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

pith.paper-citation-record.v1
1606.04820 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:37:04.223650Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T10:52:44.325275Z

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 15f2001b-ba0f-48ec-bcaa-1a0442afcb77 · inbound

Machine-learnt potential highlights melting and freezing of aluminium nanoparticles cites this paper.

Machine-learnt potential highlights melting and freezing of aluminium nanoparticles Understanding Probabilistic Sparse Gaussian Process Approximations

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:52:44.331176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T10:52:44.100186Z digest=sha256:074b0b16b6dc304f46c1a95169be003aa2da9126fb012c4b46673be4e7c49daa

Observation 6c10ac79-44e7-4881-b7cc-c3bbc9e88b0d · inbound

Evaluating Uncertainty in Deep Gaussian Processes cites this paper.

Evaluating Uncertainty in Deep Gaussian Processes Understanding Probabilistic Sparse Gaussian Process Approximations

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T10:37:04.223650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:37:04.223650Z digest=sha256:6add57d88a43ec7b10fe5349e82cc0377a5554d6224ab92eed9767daa1dd7638