Paper Citation Record · LEDGER

The Variational Gaussian Process

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1511.06499.

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

pith.paper-citation-record.v1
1511.06499 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:50:56.036212Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T22:08:20.679089Z

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 4118ddc8-1ee1-4ca2-a164-fc549431b726 · inbound

Density estimation using Real NVP cites this paper.

Density estimation using Real NVP The Variational Gaussian Process

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:57:54.394283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 11c6938a-1b51-408b-94de-1d002f4e6673 · inbound

Seismic tomography using variational inference methods cites this paper.

Seismic tomography using variational inference methods The Variational Gaussian Process

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-14T11:45:22.031384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d1e2665-3c0a-47bd-b708-d43353bb07d5 · inbound

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs cites this paper.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs The Variational Gaussian Process

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T11:08:46.330965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9763709c-6b80-4d9c-8840-3b43a1535995 · inbound

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning cites this paper.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning The Variational Gaussian Process

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-09T12:38:14.316160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c496b98-f9e3-41ee-ab5b-e5b736cf122c · inbound

A cautious user's guide in applying HMMs to physical systems cites this paper.

A cautious user's guide in applying HMMs to physical systems The Variational Gaussian Process

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:28.518364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e80a6fdf-47e3-4058-8a51-9f9fd9162ad7 · inbound

Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial cites this paper.

Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial The Variational Gaussian Process

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:57:54.394283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 565879a2-64de-4fdb-bbba-5f69d2e10d17 · inbound

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language cites this paper.

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language The Variational Gaussian Process

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T14:50:56.036212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.