Paper Citation Record · LEDGER

Gaussian Process Regression Networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 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 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:16:35.562296Z

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 eb5ff792-9d7e-4b79-bc01-1083fe38fb36 · inbound

Deep Kernel Learning for Clustering cites this paper.

Deep Kernel Learning for Clustering Gaussian Process Regression Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T14:16:35.562296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-18T06:34:40.430872+00:00.

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.