Paper Citation Record · LEDGER

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2106.03609.

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

pith.paper-citation-record.v1
2106.03609 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:09:59.959747Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T13:01:23.706994Z

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 a5311b50-8f1d-47c2-a6ce-8b7ccb04e4a4 · inbound

Learned Offline Query Planning via Bayesian Optimization cites this paper.

Learned Offline Query Planning via Bayesian Optimization High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T20:09:59.959747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b8e8280-6e82-4143-8bcd-c8fd07ac6817 · inbound

Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces cites this paper.

Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T20:09:09.551163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d8c6bff-c68e-4c3b-b18e-b3fa420a0b13 · inbound

Natural Evolutionary Search meets Probabilistic Numerics cites this paper.

Natural Evolutionary Search meets Probabilistic Numerics High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:51:16.433946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c726dc36-5b44-49ef-87c1-86a32af90316 · inbound

Sample-Efficient Optimisation over the Outputs of Generative Models cites this paper.

Sample-Efficient Optimisation over the Outputs of Generative Models High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:01:23.709758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b5fa8312-e65f-4543-99d8-94e19c0f9305 · inbound

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs cites this paper.

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:11:23.324568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0013a60f-1e8c-46d2-a8ca-93b3d2e99c88 · inbound

Optimization of time-consuming experimental conditions using pseudo-experimental data guided by adaptive polynomial regression cites this paper.

Optimization of time-consuming experimental conditions using pseudo-experimental data guided by adaptive polynomial regression High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T05:27:39.454377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.