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Paper Citation Record · LEDGER

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences

As of 14 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 1 inbound Pith citation observation for arXiv:2601.22890.

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

pith.paper-citation-record.v1
2601.22890 v1

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measured 76 of 76 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

76 of 76 outbound references displayed

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External citation measurements

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Outbound references

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This paper cites WIREs Computational Statistics16(1), 1645 (2024) https://doi.org/10.1002/wics.1645 https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1645.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences WIREs Computational Statistics16(1), 1645 (2024) https://doi.org/10.1002/wics.1645 https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1645

Reference 1

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This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology)63(3), 425–464 (2001).

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Journal of the Royal Statistical Society: Series B (Statistical Methodology)63(3), 425–464 (2001)

Reference 2

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This paper cites Journal of Computational Physics545, 114469 (2026) https://doi.org/10.1016/ j.jcp.2025.114469.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Journal of Computational Physics545, 114469 (2026) https://doi.org/10.1016/ j.jcp.2025.114469

Reference 3

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This paper cites https://arxiv.org/abs/2509.18998.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences https://arxiv.org/abs/2509.18998

Reference 4

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This paper cites Automatica39(4), 669–676 (2003) https://doi.org/10.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Automatica39(4), 669–676 (2003) https://doi.org/10

Reference 5

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This paper cites PLOS Computational Biology19(11), 1–26 (2023) https: //doi.org/10.1371/journal.pcbi.1011111.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences PLOS Computational Biology19(11), 1–26 (2023) https: //doi.org/10.1371/journal.pcbi.1011111

Reference 6

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This paper cites SIAM Journal on Scientific Computing26(2), 448–466 (2004) https://doi.org/10.1137/ S1064827503426693.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences SIAM Journal on Scientific Computing26(2), 448–466 (2004) https://doi.org/10.1137/ S1064827503426693

Reference 7

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This paper cites Journal of the American Statistical Association 103(482), 570–583 (2008) https://doi.org/10.1198/016214507000000888.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Journal of the American Statistical Association 103(482), 570–583 (2008) https://doi.org/10.1198/016214507000000888

Reference 8

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This paper cites Archives of Computational Methods in Engineering27(2), 361–385 (2020) https://doi.org/ 10.1007/s11831-018-09311-x.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Archives of Computational Methods in Engineering27(2), 361–385 (2020) https://doi.org/ 10.1007/s11831-018-09311-x

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This paper cites Journal of the Mechanics and Physics of Solids149, 104284 (2021) https://doi.org/10.1016/j.jmps.2020.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Journal of the Mechanics and Physics of Solids149, 104284 (2021) https://doi.org/10.1016/j.jmps.2020

Reference 10

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This paper cites Bayesian Analysis1(4), 765–792 (2006) https://doi.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Bayesian Analysis1(4), 765–792 (2006) https://doi

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Reliability Engineering & System Safety91(10), 1290–1300 (2006) https://doi.org/10.1016/ j.ress.2005.11.025

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This paper cites SAE International Journal of Passenger Cars - Mechanical Systems8(2), 415–420 (2015) https://doi.org/10.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences SAE International Journal of Passenger Cars - Mechanical Systems8(2), 415–420 (2015) https://doi.org/10

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This paper cites Energy and Buildings174, 527–547 (2018) https://doi.org/10.

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Energy and Buildings174, 527–547 (2018) https://doi.org/10

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Bul- letin of Mathematical Biology79(4), 939–974 (2017) https://doi.org/10.1007/ s11538-017-0258-5

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Archives of Computational Methods in Engineering30(5), 2859–2888 (2023) https://doi.org/10.1007/s11831-023-09888-y

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Materials13(19) (2020) https://doi

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Geosci- entific Model Development18(20), 7501–7527 (2025) https://doi.org/10.5194/ gmd-18-7501-2025

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This paper cites Journal of Machine Learning Research24, 1–35 (2023).

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Journal of Machine Learning Research24, 1–35 (2023)

Reference 20

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Preprint, University of Luxembourg (2024)

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Calibration of multi-physics computational models using Bayesian networks

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Bayesian Analysis, 1–30 (2022) https://doi.org/10.1214/21-BA1293

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Software (2018)

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences PeerJ Computer Science2, 55 (2016) https://doi.org/10.7717/ peerj-cs.55

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Supercurrent Reversal in Two-Dimensional Topological Insulators

Reference 32

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Communi- cations in Applied Mathematics and Computational Science5(1), 65–80 (2010) https://doi.org/10.2140/camcos.2010.5.65

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Effective Sample Size for Importance Sampling based on discrepancy measures

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Statistical Science7(4), 457–472 (1992) https://doi.org/10.1214/ss/ 1177011136

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Statistical Science36(4), 518–529 (2021) https://doi.org/10.1214/20-STS812

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences Bayesian Analysis16(2) (2021) https://doi.org/10

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A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences The American Eco- nomic Review18(1), 139–165 (1928)

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Reference 76

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Bayesian reversal of the liquid level trajectory in a draining tank for pollution forensics A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences

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