Paper Citation Record · LEDGER

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2512.18066.

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

pith.paper-citation-record.v1
2512.18066 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:11:19.635129Z

measured 17 of 17 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T13:40:28.374528Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy0
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99fe4c70-b3d1-4fee-86cf-e34d192efa6f · outbound

This paper cites Nonstationary Gaussian Process Surrogates.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Nonstationary Gaussian Process Surrogates

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.358073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f848e6e6-3c4e-44e3-b3f0-5cfcd5bb20b6 · outbound

This paper cites All Emulators are Wrong, Many are Useful, and Some are More Useful Than Others: A Reproducible Comparison of Computer Model Surrogates.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments All Emulators are Wrong, Many are Useful, and Some are More Useful Than Others: A Reproducible Comparison of Computer Model Surrogates

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.034832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfb705d5-b39b-4a82-9fdb-89cf7997a5bb · outbound

This paper cites Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.466181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e4bdc27-f4f9-413b-b708-345e7f2dec2d · outbound

This paper cites On the instability issue of gradient-enhanced Gaussian process emulators for computer experiments.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments On the instability issue of gradient-enhanced Gaussian process emulators for computer experiments

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.718088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74bf3478-6530-4e1e-afd8-e3867f78b8df · outbound

This paper cites Empirical assessment of deep gaussian process surrogate models for engineering problems.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Empirical assessment of deep gaussian process surrogate models for engineering problems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.948299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b204a5ba-c430-4f4f-99ee-78f8fc597561 · outbound

This paper cites Vecchia-approximated deep Gaussian processes for computer experiments.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Vecchia-approximated deep Gaussian processes for computer experiments

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.215639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5132b599-56f1-481e-bc05-dfb56d9ebf37 · outbound

This paper cites Gradient-enhanced reliability analysis of transonic aeroelastic flutter.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Gradient-enhanced reliability analysis of transonic aeroelastic flutter

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.302402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f65bd6f5-1cbd-4b1a-802e-2e323461d7e4 · outbound

This paper cites Bayesian optimization with gradients.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Bayesian optimization with gradients

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.554748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c04ea345-be9b-4841-b12e-1130e7552a01 · outbound

This paper cites Deep Gaussian Process Emulation with gradient Information and Sequential Design for Simulators with Sharp Variations.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Deep Gaussian Process Emulation with gradient Information and Sequential Design for Simulators with Sharp Variations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.635129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c29c609-fab9-4044-be50-58a86fe30d8e · outbound

This paper cites J., Williams, B.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments J., Williams, B

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.121290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9360e61-44e4-4934-b1bf-265cee4748a6 · outbound

This paper cites Strictly proper scoring rules, prediction, and estimation.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Strictly proper scoring rules, prediction, and estimation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.633156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d6a41ed-c9e1-46eb-8e1a-a8d22afbc6fd · outbound

This paper cites Deep Gaussian processes for calibration of computer models (with discussion).

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Deep Gaussian processes for calibration of computer models (with discussion)

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.856052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31f1d467-3bdc-4bcc-a74b-9d7073e458a4 · outbound

This paper cites Asymptotic properties of Vecchia approximation for Gaussian processes.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Asymptotic properties of Vecchia approximation for Gaussian processes

Reference 282

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.795996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e837494a-3369-41f0-8ca9-e9981fd780c7 · outbound

This paper cites Validated reduced computational methods for realistic RDC injection modeling.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Validated reduced computational methods for realistic RDC injection modeling

Reference 632

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.391256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c0a8d37-af92-4b4a-b533-c5210211d123 · outbound

This paper cites Estimation and model identification for continuous spatial processes.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Estimation and model identification for continuous spatial processes

Reference 1033

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:19.486308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4fd48ed-e244-4a68-bc50-6d5e8100a641 · outbound

This paper cites Scaling Gaussian process regression with derivatives.

Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments Scaling Gaussian process regression with derivatives

Reference 2276

Resolution: unresolved; no resolver link, observed 2026-08-03T15:11:18.570937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f50018f4-a432-4278-8946-237e52fa113b · inbound

Profile Bayesian Optimization for Expensive Computer Experiments cites this paper.

Profile Bayesian Optimization for Expensive Computer Experiments Gradient-enhancement and Gradient Predictions for Deep Gaussian Process Modeling of Expensive Computer Experiments

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T13:40:28.374528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.