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Paper Citation Record · LEDGER

Gaussian Process Regression Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1110.4411.

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

pith.paper-citation-record.v1
1110.4411 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:55:36.346933Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T05:38:54.551320Z

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 abee0f14-88fb-41b5-bb4d-19a5b5d96440 · inbound

Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process cites this paper.

Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process Gaussian Process Regression Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T20:34:58.004159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:34:58.004159Z digest=sha256:73664de05eec8ce5c12fcfa4c994d38f153eecce932c8a142f99b05b940995e5

Observation b55e802d-8154-4345-81c9-05e945a9d06e · inbound

Convolution-Based Converter : A Weak-Prior Approach For Modeling Stochastic Processes Based On Conditional Density Estimation cites this paper.

Convolution-Based Converter : A Weak-Prior Approach For Modeling Stochastic Processes Based On Conditional Density Estimation Gaussian Process Regression Networks

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-09T05:38:54.556820Z

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.

source=arxiv_source observed=2026-08-09T05:38:54.519510Z digest=sha256:8677ea4640c8e4d7ff06706fc3f143ecb75dd2425233a6e3a4bc85ad1533bb08

Observation 4ebfd26e-7289-4845-b709-0cd5b0ba03be · inbound

A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties cites this paper.

A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties Gaussian Process Regression Networks

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-11T12:55:36.346933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:55:36.346933Z digest=sha256:8624774e2274a9b831d030ac46beb1a8235c15827763fb5c420debabbdef28d5