Paper Citation Record · LEDGER

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions

As of 18 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.04392.

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

pith.paper-citation-record.v1
2412.04392 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:33:34.679747Z

measured 31 of 31 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 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

31 of 31 outbound references displayed

verified exact11
verified fuzzy9
unresolved8
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ccb5911-04c9-44e0-a1f4-d3629c95ef6b · outbound

This paper cites ComptesRendus Hebd.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions ComptesRendus Hebd

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.658489Z

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.

Observation 823c7d1f-3412-4bd2-9f81-c095fbb13e21 · outbound

This paper cites an unresolved cited work.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Unresolved cited work

Reference 2

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T21:33:35.921373Z

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.

Observation bea23f67-3cc4-4ff3-be4f-4fb0b6f14f80 · outbound

This paper cites A review on genetic algorithm: past, present, and future.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions A review on genetic algorithm: past, present, and future

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.186253Z

Source-reported events for the cited work

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Observation cf8d2249-650d-4202-b19f-448a568ab28d · outbound

This paper cites Recent Advances in Bayesian Optimization.ACM Comput.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Recent Advances in Bayesian Optimization.ACM Comput

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.219405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c2e2675-b68e-4faa-a6fc-4a54fa931fca · outbound

This paper cites An improved PSO-based charging strategy of electric vehicles in electrical distribution grid.Appl.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions An improved PSO-based charging strategy of electric vehicles in electrical distribution grid.Appl

Reference 5

Resolution: verified exact; doi, observed 2026-08-11T21:33:35.053431Z

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.

Observation 594f2787-939e-41e9-9521-15bc6d06155f · outbound

This paper cites Multi-objective optimal design of hybrid renewable energy systems usingPSO-simulationbasedapproach.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Multi-objective optimal design of hybrid renewable energy systems usingPSO-simulationbasedapproach

Reference 6

Resolution: malformed identifier; no resolver link, observed 2026-08-11T21:33:34.312731Z

Source-reported events for the cited work

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Observation 8b296711-83f3-44ee-a2cc-750190974228 · outbound

This paper cites Using genetic algorithm (GA) and particle swarm optimization (PSO) methodsfordeterminationofinteractionparametersinmulticomponentsystemsofliquid–liquidequilibria.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Using genetic algorithm (GA) and particle swarm optimization (PSO) methodsfordeterminationofinteractionparametersinmulticomponentsystemsofliquid–liquidequilibria

Reference 7

Resolution: verified exact; doi, observed 2026-08-11T21:33:35.026924Z

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.

Observation c82b5530-c09c-42bc-8e53-f141a1181827 · outbound

This paper cites Response surface methodology (RSM) as a tool for optimization in analytical chemistry.Talanta, 76 (5) : 965–977,doi: https://doi.org/10.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Response surface methodology (RSM) as a tool for optimization in analytical chemistry.Talanta, 76 (5) : 965–977,doi: https://doi.org/10

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.643343Z

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.

Observation 6ac96ae0-f4cf-4c7a-a185-3214e13f2dcd · outbound

This paper cites Application of response surface methodology (RSM) to optimize coagulation-flocculation treatment of leachate using poly-aluminum chloride (PAC) and alum.J.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Application of response surface methodology (RSM) to optimize coagulation-flocculation treatment of leachate using poly-aluminum chloride (PAC) and alum.J

Reference 9

Resolution: verified exact; doi, observed 2026-08-11T21:33:35.008129Z

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.

Observation 891d912e-9b6f-4311-8775-2725b4abf584 · outbound

This paper cites Application of RSM for optimization of glutamic acid productionby Corynebacteriumglutamicum inbathculture.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Application of RSM for optimization of glutamic acid productionby Corynebacteriumglutamicum inbathculture

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.627964Z

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.

Observation 91fde45f-ec45-4def-bb60-36db9c2cee6c · outbound

This paper cites On the Experimental Attainment of Optimum Conditions.J.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions On the Experimental Attainment of Optimum Conditions.J

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.459571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f418af6-4b37-4d61-aa2c-e377ec493b6c · outbound

This paper cites Some New Three Level Designs for the Study of Quantitative Variables.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Some New Three Level Designs for the Study of Quantitative Variables

Reference 12

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.874401Z

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.

Observation 401f02b7-bb60-4b9c-b946-3c9e4374ef59 · outbound

This paper cites A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise.J.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise.J

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.469477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0f5d4f2-c0df-4d3f-9a08-7ecd8ae5484f · outbound

This paper cites Bayesian Optimization for Adaptive Experimental Design: A Review.IEEE Access, 8 : 13937–13948,doi: https://doi.org/10.1109/ACCESS.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Bayesian Optimization for Adaptive Experimental Design: A Review.IEEE Access, 8 : 13937–13948,doi: https://doi.org/10.1109/ACCESS

Reference 14

Resolution: malformed identifier; no resolver link, observed 2026-08-11T21:33:34.474594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c2ea94-fd04-4774-a9a5-37127a5900c1 · outbound

This paper cites A survey of adaptive sampling for global metamodeling in support of simulation-basedcomplexengineeringdesign.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions A survey of adaptive sampling for global metamodeling in support of simulation-basedcomplexengineeringdesign

Reference 15

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.816501Z

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.

Observation 6dadd1a2-933e-49a7-9c87-a2e449e7a9d8 · outbound

This paper cites A Customized Bayesian Algorithm to Optimize Enzyme-Catalyzed Reactions.ACS Sustain.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions A Customized Bayesian Algorithm to Optimize Enzyme-Catalyzed Reactions.ACS Sustain

Reference 16

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.800251Z

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.

Observation e9f62277-742f-45f3-ad64-d540276cdff8 · outbound

This paper cites Bayesian cell therapy process optimization.Biotechnol.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Bayesian cell therapy process optimization.Biotechnol

Reference 17

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.783037Z

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.

Observation df6d6183-813c-4dd5-95bc-90e65c5e4497 · outbound

This paper cites an unresolved cited work.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Unresolved cited work

Reference 18

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.767780Z

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.

Observation 7a0cc899-40fe-405c-869c-ca13b01bd746 · outbound

This paper cites Batch Bayesian Optimization via Local Penalization.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Batch Bayesian Optimization via Local Penalization

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.610583Z

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.

Observation 74b17623-6642-4caf-ac8d-567f0e65056b · outbound

This paper cites The Parallel Knowledge Gradient Method for Batch Bayesian Optimization.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.467358Z

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.

Observation eae68db5-dcbe-483f-beda-6745ee584302 · outbound

This paper cites Sequential statistical optimization of lactose–based medium and process variables for inulinase production fromPenicillium oxalicumBGPUP-4.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Sequential statistical optimization of lactose–based medium and process variables for inulinase production fromPenicillium oxalicumBGPUP-4

Reference 21

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.751450Z

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.

Observation 84dc1598-6a76-40b5-b9cc-3510f3336c43 · outbound

This paper cites Pipeline Architecture.ACM Comput.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Pipeline Architecture.ACM Comput

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.511682Z

Source-reported events for the cited work

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Observation 999343ff-3e1c-47df-8017-a7923c282d7e · outbound

This paper cites Real-Parameter Black-Box Optimization Benchmarking 2009: Noiseless Functions Definitions.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Real-Parameter Black-Box Optimization Benchmarking 2009: Noiseless Functions Definitions

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.327799Z

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.

Observation 0cc4c1da-f58a-483d-b35f-4a1fda9f54e7 · outbound

This paper cites Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation.Proceedings of the 36th International Conference on Machine Learning, 97 : 253–262, PMLR.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation.Proceedings of the 36th International Conference on Machine Learning, 97 : 253–262, PMLR

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.310287Z

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.

Observation 8e8e4086-b801-4be4-bc9b-fe2a1aaaf7b0 · outbound

This paper cites Methods and Softw., 36 : 114–144,doi: https://doi.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Methods and Softw., 36 : 114–144,doi: https://doi

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.523703Z

Source-reported events for the cited work

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Observation 91fd5d64-d6ea-4d99-9567-a9bd4000aaf7 · outbound

This paper cites Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator.ACM Trans.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator.ACM Trans

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T21:33:34.528205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6568bc3-296c-4aa3-9017-420ce970b937 · outbound

This paper cites an unresolved cited work.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:33:36.294092Z

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.

Observation 3175806c-f174-45d5-8617-42807053047c · outbound

This paper cites GPyOpt: A Bayesian Optimization framework in python.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions GPyOpt: A Bayesian Optimization framework in python

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.263951Z

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.

Observation d08e6b05-fe13-4b7e-aab9-0a3c66fdf682 · outbound

This paper cites Parallelised Bayesian Optimisation via Thompson Sampling.Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, 84 : 133–142, PMLR.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Parallelised Bayesian Optimisation via Thompson Sampling.Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, 84 : 133–142, PMLR

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:33:36.095337Z

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.

Observation f811f2cb-84d4-448f-8297-307f7b4d4094 · outbound

This paper cites Optimal Scheduling for Laboratory Automation of Life Science Experiments with Time Constraints.SLAS Technol., 26 (6) : 650–659,doi: https: //doi.org/10.1177/24726303211021790.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions Optimal Scheduling for Laboratory Automation of Life Science Experiments with Time Constraints.SLAS Technol., 26 (6) : 650–659,doi: https: //doi.org/10.1177/24726303211021790

Reference 30

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.735799Z

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.

Observation 9d1276a5-3b76-4ffd-865e-6ee2adcb392c · outbound

This paper cites SAGAS: Simulated annealing and greedy algorithm scheduler for laboratory automation.SLAS Technol., 28 (4) : 264–277,doi: https://doi.

Asynchronous Batch Bayesian Optimization with Pipelining Evaluations for Experimental Resource$\unicode{x2013}$constrained Conditions SAGAS: Simulated annealing and greedy algorithm scheduler for laboratory automation.SLAS Technol., 28 (4) : 264–277,doi: https://doi

Reference 31

Resolution: verified exact; doi, observed 2026-08-11T21:33:34.717848Z

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.

Pith citing papers

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