Paper Citation Record · LEDGER

New Bounds for Sparse Variational Gaussian Processes

As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2502.08730.

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

pith.paper-citation-record.v1
2502.08730 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:02:48.056294Z

measured 15 of 15 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy10
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51ebc8ac-b591-4ee0-8060-70a9be186a54 · outbound

This paper cites 14 By maximizing wrt v we obtain v∗ = 1 +tr(Kff−Qff) N σ2 −1 , and by substituting this back into the bound we obtain Artemev et al.

New Bounds for Sparse Variational Gaussian Processes 14 By maximizing wrt v we obtain v∗ = 1 +tr(Kff−Qff) N σ2 −1 , and by substituting this back into the bound we obtain Artemev et al

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.306570Z

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.

Observation 57a0fc50-f233-457f-a024-1f6c8e4801e8 · outbound

This paper cites (27) where we highlighted with blue a term in the third line to contrast it with a similar term when proving Lemma 3.2 in Appendix B.4.

New Bounds for Sparse Variational Gaussian Processes (27) where we highlighted with blue a term in the third line to contrast it with a similar term when proving Lemma 3.2 in Appendix B.4

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.326094Z

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.

Observation 68737c00-23aa-4050-bd68-fcc610aa47b6 · outbound

This paper cites σ2 σ2 f ℓ2 Exact GP 0.0715 0.712 0.597 SVGP-new 0.087 0.485 0.615 SVGP 0.108 0.331 0.617 D.

New Bounds for Sparse Variational Gaussian Processes σ2 σ2 f ℓ2 Exact GP 0.0715 0.712 0.597 SVGP-new 0.087 0.485 0.615 SVGP 0.108 0.331 0.617 D

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.296394Z

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.

Observation edf4c6cf-c62b-43f2-a4d3-f1f27a983d58 · outbound

This paper cites Lloyd, C., Gunter, T., Osborne, M., and Roberts, S.

New Bounds for Sparse Variational Gaussian Processes Lloyd, C., Gunter, T., Osborne, M., and Roberts, S

Reference 4

Resolution: metadata mismatch; raw_fallback, observed 2026-08-08T00:02:48.226577Z

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.

Observation d0ea31f4-1b12-414f-9e77-51444c3b1c82 · outbound

This paper cites Now since V is a diagonal matrix we have tr(V(Kff − Qff)) =PN i=1 vi(kii − qii) which completes the proof.

New Bounds for Sparse Variational Gaussian Processes Now since V is a diagonal matrix we have tr(V(Kff − Qff)) =PN i=1 vi(kii − qii) which completes the proof

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.316727Z

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.

Observation baf3dc75-d0d9-47dc-8797-9b9690816fe0 · outbound

This paper cites SGPR methods use M = 2048 inducing points initialized by k-means.

New Bounds for Sparse Variational Gaussian Processes SGPR methods use M = 2048 inducing points initialized by k-means

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.267664Z

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.

Observation af877bfa-c791-4eea-aaf2-376080451966 · outbound

This paper cites Best mean values are highlighted.

New Bounds for Sparse Variational Gaussian Processes Best mean values are highlighted

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.258824Z

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.

Observation 3b2c6d72-c34c-4f4d-8f88-2009c5481ca6 · outbound

This paper cites (2020)) isN = 11122(with d =.

New Bounds for Sparse Variational Gaussian Processes (2020)) isN = 11122(with d =

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.286813Z

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.

Observation 17e06be9-1fd1-4753-9e04-6939e12d48d8 · outbound

This paper cites Large scale regression datasets The experimental settings are chosen to match the ones from Wang et al.

New Bounds for Sparse Variational Gaussian Processes Large scale regression datasets The experimental settings are chosen to match the ones from Wang et al

Reference 1024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.277272Z

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.

Observation 5694f589-88ee-432d-910c-37af8bcfd07f · outbound

This paper cites and Rasmussen, C.

New Bounds for Sparse Variational Gaussian Processes and Rasmussen, C

Reference 1978

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.343889Z

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.

Observation c8ab93d7-571d-47b7-b619-312ad318b8b5 · outbound

This paper cites A Tutorial on Sparse Gaussian Processes and Variational Inference.

New Bounds for Sparse Variational Gaussian Processes A Tutorial on Sparse Gaussian Processes and Variational Inference

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:48.015076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8701f387-8c29-422f-9724-07158e0975cf · outbound

This paper cites Shi, J., Titsias, M.

New Bounds for Sparse Variational Gaussian Processes Shi, J., Titsias, M

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:48.334926Z

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.

Observation 3436ceb7-49a7-4d98-9937-4933c534f926 · outbound

This paper cites Gaussian Processes for Big Data.

New Bounds for Sparse Variational Gaussian Processes Gaussian Processes for Big Data

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:48.011017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f07c41ff-4145-4def-a9d5-7e8df9d1d31b · outbound

This paper cites Deep Gaussian Processes with Decoupled Inducing Inputs.

New Bounds for Sparse Variational Gaussian Processes Deep Gaussian Processes with Decoupled Inducing Inputs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:48.006251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79706993-7e97-4624-9a0e-f9fdbdaed18a · outbound

This paper cites Exact Gaussian Processes on a Million Data Points.

New Bounds for Sparse Variational Gaussian Processes Exact Gaussian Processes on a Million Data Points

Reference 2021

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T00:02:48.161749Z

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.

Pith citing papers

No inbound Pith citation observations are available.