Paper Citation Record · LEDGER

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs

As of 22 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2504.13441.

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

pith.paper-citation-record.v1
2504.13441 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:11:45.234359Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

37 of 37 outbound references displayed

verified exact1
verified fuzzy36
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1086cca-e74f-4885-9de3-68257dd47e7f · outbound

This paper cites Using confidence bounds for exploitation-exploration trade-offs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Using confidence bounds for exploitation-exploration trade-offs

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.815147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c5cbf98a-6faf-479c-8767-8dc31858df6c · outbound

This paper cites Sequential design of computer experiments for the estimation of a probability of failure.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Sequential design of computer experiments for the estimation of a probability of failure

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.796720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0bb1fd9b-e769-49f3-ad65-85d5fc2ed6ee · outbound

This paper cites Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.780507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2d7f6e2f-82e4-49f9-a169-96314595c6da · outbound

This paper cites Moana: Modeling and analyzing I/O variability in parallel system experimental design.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Moana: Modeling and analyzing I/O variability in parallel system experimental design

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.766576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4602927c-468a-421a-b038-160ba12e02dc · outbound

This paper cites Latin Hypercube Samples.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Latin Hypercube Samples

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.752231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a9b24a3-907b-4510-8800-b197ad0cbce3 · outbound

This paper cites Entropy-based adaptive design for contour finding and estimating reliability.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Entropy-based adaptive design for contour finding and estimating reliability

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.736549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a051aa72-4a7f-4aaa-b119-9386a7cd7aaf · outbound

This paper cites Additive Gaussian process for computer models with qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Additive Gaussian process for computer models with qualitative and quantitative factors

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.718103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4fed4c95-3a99-47b3-a6d8-87a2331b18b0 · outbound

This paper cites Design for computer experiments with qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Design for computer experiments with qualitative and quantitative factors

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.704594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d121bca-af53-48f9-8ef6-f0050c6b5ca3 · outbound

This paper cites Surrogates: Gaussian process modeling, design, and optimization for the applied sciences.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Surrogates: Gaussian process modeling, design, and optimization for the applied sciences

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.690042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6e68d285-e96f-4d92-9c3c-e9afd6b59970 · outbound

This paper cites Prediction for computer experiments having quantitative and qualitative input variables.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Prediction for computer experiments having quantitative and qualitative input variables

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.674546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation df368e22-3398-4d10-a892-440323f3ea28 · outbound

This paper cites On construction of marginality coupled designs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs On construction of marginality coupled designs

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.660442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c0e929f-f709-40d6-ba77-17bbc5b833c7 · outbound

This paper cites Marginally coupled designs for two-level qualitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Marginally coupled designs for two-level qualitative factors

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.646311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 05867a45-6060-4437-8bcc-5b35804aee28 · outbound

This paper cites Predictive entropy search for efficient global optimization of black-box functions.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Predictive entropy search for efficient global optimization of black-box functions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.632881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1155160b-1e49-4756-b6e6-a9713429cd0e · outbound

This paper cites Sliced orthogonal array-based Latin hypercube designs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Sliced orthogonal array-based Latin hypercube designs

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.619807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 26ccf7b3-988e-4a2a-8e98-02d555ffb8f5 · outbound

This paper cites Efficient global optimization of expensive black-box functions.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Efficient global optimization of expensive black-box functions

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.606199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f6e3c2ae-d454-4a7f-b1eb-d75394931303 · outbound

This paper cites Bandit based Monte - Carlo planning.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Bandit based Monte - Carlo planning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.593473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8197c189-f347-4991-900b-0fa026689445 · outbound

This paper cites Devon Lin, and Xinwei Deng.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Devon Lin, and Xinwei Deng

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.579828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8ed3805b-d7e5-4bd9-a77e-6ebeae46dec0 · outbound

This paper cites Category tree Gaussian process for computer experiments with many-category qualitative factors and application to cooling system design.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Category tree Gaussian process for computer experiments with many-category qualitative factors and application to cooling system design

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.565683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 14cfef6a-6fee-4be8-9d91-5766a1d4013e · outbound

This paper cites Hybrid parameter search and dynamic model selection for mixed-variable Bayesian optimization.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Hybrid parameter search and dynamic model selection for mixed-variable Bayesian optimization

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.551845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e358b76e-7457-4fab-807e-f3ae5db18174 · outbound

This paper cites A comparison of three methods for selecting values of input variables in the analysis of output from a computer code.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs A comparison of three methods for selecting values of input variables in the analysis of output from a computer code

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.536744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 68241650-ef02-43b0-afb2-3219dc54df53 · outbound

This paper cites Genetic Optimization Using Derivatives.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Genetic Optimization Using Derivatives

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.522309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 49720d31-5a3f-424c-816c-57154419216c · outbound

This paper cites Cross-validation--based adaptive sampling for Gaussian process models.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Cross-validation--based adaptive sampling for Gaussian process models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.507950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1bcc3837-eefb-4c09-bbdd-af14f1f6973e · outbound

This paper cites Quantile-based optimization of noisy computer experiments with tunable precision.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Quantile-based optimization of noisy computer experiments with tunable precision

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.494299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1be37438-f615-461f-bbaf-affdff710854 · outbound

This paper cites Gaussian process models for computer experiments with qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Gaussian process models for computer experiments with qualitative and quantitative factors

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.482311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1bc2c2dc-2168-4b15-91fc-552f30177623 · outbound

This paper cites Sliced Latin hypercube designs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Sliced Latin hypercube designs

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.470396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d530c102-a135-4968-8b5f-ba22f259a7ca · outbound

This paper cites Sequential experiment design for contour estimation from complex computer codes.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Sequential experiment design for contour estimation from complex computer codes

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.458003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ff348ccd-3682-4d0c-9481-6a4a623b335d · outbound

This paper cites Design and analysis of computer experiments.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Design and analysis of computer experiments

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.444321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9e0dd315-962b-49d0-b0e9-db952f8cd3f1 · outbound

This paper cites Adaptive Design for Contour Estimation from Computer Experiments with Quantitative and Qualitative Inputs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Adaptive Design for Contour Estimation from Computer Experiments with Quantitative and Qualitative Inputs

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:11:45.286599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5a4d7244-6883-42b3-ad6c-83373de7e02a · outbound

This paper cites Gaussian process optimization in the bandit setting: No regret and experimental design.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Gaussian process optimization in the bandit setting: No regret and experimental design

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.430569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8827c330-f989-46ce-9d8a-6a48293d9eb6 · outbound

This paper cites EzGP : Easy-to-interpret Gaussian process models for computer experiments with both quantitative and qualitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs EzGP : Easy-to-interpret Gaussian process models for computer experiments with both quantitative and qualitative factors

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.415157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 39a88729-ff56-4a0c-a1a9-2e5f26bdd8b7 · outbound

This paper cites Global fitting of the response surface via estimating multiple contours of a simulator.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Global fitting of the response surface via estimating multiple contours of a simulator

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.400988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c2eb49a-3a62-4160-b03b-da3f66337eb4 · outbound

This paper cites Doubly coupled designs for computer experiments with both qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Doubly coupled designs for computer experiments with both qualitative and quantitative factors

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.387710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fe5c5cb5-0a1f-4233-813a-6f80f640d8c2 · outbound

This paper cites Construction of sliced orthogonal Latin hypercube designs.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Construction of sliced orthogonal Latin hypercube designs

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.372345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 672a1154-04b1-4c9d-a306-207353146bbb · outbound

This paper cites Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.356959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d0090e91-a2a0-4e35-99a3-5f4327c8e7d9 · outbound

This paper cites Bayesian optimization for materials design with mixed quantitative and qualitative variables.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs Bayesian optimization for materials design with mixed quantitative and qualitative variables

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.343882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9cbf684f-6d0b-453b-bb85-0277fa98836f · outbound

This paper cites A latent variable approach to Gaussian process modeling with qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs A latent variable approach to Gaussian process modeling with qualitative and quantitative factors

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.323901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1f07d16d-fe91-4d7f-97b8-49cd20ba3a99 · outbound

This paper cites A simple approach to emulation for computer models with qualitative and quantitative factors.

Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs A simple approach to emulation for computer models with qualitative and quantitative factors

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:11:45.309525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.