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Paper Citation Record · LEDGER

Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2104.11667.

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

pith.paper-citation-record.v1
2104.11667 v4

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

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:52:23.552142Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T08:40:32.981947Z

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 7d499923-6029-478b-9ac2-5f56f72f0104 · inbound

General Inverse Design of Thin-Film Metamaterials With Convolutional Neural Networks cites this paper.

General Inverse Design of Thin-Film Metamaterials With Convolutional Neural Networks Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:40:32.984459Z

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.

source=arxiv_source observed=2026-05-25T08:38:03.408148Z digest=sha256:3e40ca83dcd233a1450e2d7b44f4dce567cad17739cdbee3ea682121d9272ef5

Observation 62ca4244-90ec-4600-aa5a-29be41d6517c · inbound

Direct Regret Optimization in Bayesian Optimization cites this paper.

Direct Regret Optimization in Bayesian Optimization Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T19:07:23.436365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:07:23.436365Z digest=sha256:6f85e49f0144e2229ab622750f0f766a8928749ab7752087b058ba2d62e4de47

Observation 37a0fc3e-480c-4953-afc1-fc615fb1e45a · inbound

Efficient Sliced Wasserstein Distance Computation via Adaptive Bayesian Optimization cites this paper.

Efficient Sliced Wasserstein Distance Computation via Adaptive Bayesian Optimization Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T15:52:23.552142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:52:23.552142Z digest=sha256:0e46f08a775deee153141170d5400d331c0675a7a81058481f43a924c8e96313