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README.md

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@@ -207,24 +207,25 @@ Dubreuil, S., Bartoli, N., Gogu, C., & Lefebvre, T. (2020).
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[Towards an efficient global multi-disciplinary design optimization algorithm](https://doi.org/10.1007/s00158-020-02514-6)
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Structural and Multidisciplinary Optimization, 62(4), 1739–1765.
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Jin, R. and Chen, W. and Sudjianto, A. (2005),
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Jin, R. and Chen, W. and Sudjianto, A. (2005).
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[An efficient algorithm for constructing optimal design of computer experiments](https://doi.org/10.1016/j.jspi.2004.02.01) Journal of Statistical Planning and Inference, 134:268-287.
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Bettebghor, Dimitri, et al.
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Bettebghor, Dimitri, et al. (2011).
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[Surrogate modeling approximation using a mixture of experts based on EM joint estimation](https://hal.archives-ouvertes.fr/hal-01852300/document)
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Structural and multidisciplinary optimization 43.2 (2011): 243-259.
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Jones, D. R., Schonlau, M., & Welch, W. J. (1998).
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[Efficient global optimization of expensive black-box functions. Journal of Global Optimization](https://www.researchgate.net/publication/235709802_Efficient_Global_Optimization_of_Expensive_Black-Box_Functions), 13(4), 455–492.
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Diouane, Youssef, et al. [TREGO: a trust-region framework for efficient global optimization](https://arxiv.org/pdf/2101.06808).
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Diouane, Youssef, et al. (2023).
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[TREGO: a trust-region framework for efficient global optimization](https://arxiv.org/pdf/2101.06808).
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Journal of Global Optimization 86.1 (2023): 1-23.
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Priem, Rémy, Nathalie Bartoli, and Youssef Diouane.
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Priem, Rémy, Nathalie Bartoli, and Youssef Diouane. (2019)
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[On the use of upper trust bounds in constrained Bayesian optimization infill criteria](https://hal.science/hal-02182492v1/file/Priem_24049.pdf).
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AIAA aviation 2019 forum. 2019.
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Sasena M., Papalambros P., Goovaerts P., 2002.
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Sasena M., Papalambros P., Goovaerts P., (2002).
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[Global optimization of problems with disconnected feasible regions via surrogate modeling](https://deepblue.lib.umich.edu/handle/2027.42/77089).
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AIAA Paper.
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@@ -234,27 +235,28 @@ Ginsbourger, D., Le Riche, R., & Carraro, L. (2010).
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E.C. Garrido-Merchan and D. Hernandez-Lobato.
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[Dealing with categorical and integer-valued variables in Bayesian Optimization with Gaussian processes](https://arxiv.org/pdf/1805.03463).
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Zhan, Dawei, et al.
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[A cooperative approach to efficient global optimization](https://link.springer.com/article/10.1007/s10898-023-01316-6). Journal of Global Optimization 88.2 (2024): 327-357
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Zhan, Dawei, et al. (2024).
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[A cooperative approach to efficient global optimization](https://link.springer.com/article/10.1007/s10898-023-01316-6).
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Journal of Global Optimization 88.2 (2024): 327-357
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Lisa Pretsch et al.
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Lisa Pretsch et al. (2025)
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[Bayesian optimization of cooperative components for multi-stage aero-structural compressor blade design](https://www.researchgate.net/publication/391492598_Bayesian_optimization_of_cooperative_components_for_multi-stage_aero-structural_compressor_blade_design). Struct Multidisc Optim 68, 84 (2025)
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Appriou, T., Rullière, D. & Gaudrie, D,
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Appriou, T., Rullière, D. & Gaudrie, D, (2024)
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[Combination of optimization-free kriging models for high-dimensional problems](https://doi.org/10.1007/s00180-023-01424-7),
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Comput Stat 39, 3049–3071 (2024).
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S. Ament, S. Daulton, D. Eriksson, M. Balandat, E. Bakshy,
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S. Ament, S. Daulton, D. Eriksson, M. Balandat, E. Bakshy, (2023).
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[Unexpected improvements to expected improvement for bayesian optimization](https://arxiv.org/pdf/2310.20708),
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Advances in Neural Information Processing Systems, 2023
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Marrel, A., & Iooss, B. (2024).
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[Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation.](https://www.sciencedirect.com/science/article/pii/S0951832024001686?casa_token=l-YuUssKYfsAAAAA:WpEZkMh7bf0Ago2rDi0I_E5BydKDTmjluPOP0KfAratwka89IRqu09U1J6OnpG1gc_8FIafRzA)
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Reliability Engineering & System Safety, 247, 110094.
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Bussemaker, Jasper H., et al. (2024)
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Bussemaker, Jasper H., et al. (2024).
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[Surrogate-based optimization of system architectures subject to hidden constraints.](https://hal.science/hal-04462408v2/file/DTIS2024-018-DTIS2024-018%20posprint-Accept%C3%A9e.pdf)
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AIAA AVIATION FORUM AND ASCEND 2024.
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AIAA Aviation forum and Ascend 2024.
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smtorg. (2018). [Surrogate modeling toolbox](https://github.com/SMTOrg/smt). GitHub.
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