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    sMF-BO-2CoGP: A Sequential Multi-Fidelity Constrained Bayesian Optimization Framework for Design Applications 

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 003
    Author(s): Tran, Anh; Wildey, Tim; McCann, Scott
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Bayesian optimization (BO) is an efiective surrogate-based method that has been widely used to optimize simulation-based applications. While the traditional Bayesian optimization approach only applies to single-fidelity ...
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    Erratum: “sMF-BO-2CoGP: A Sequential Multi-Fidelity Constrained Bayesian Optimization Framework for Design Applications” [ASME J. Comput. Inf. Sci. Eng., 20(3), p. 0031007; DOI: 10.1115/1.4046691] 

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 005:;page 057001-1
    Author(s): Tran, Anh; Wildey, Tim; McCann, Scott
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This article was intended to be published as part of the October 2020 Special Issue on Highlights of 2020 CIE Conference.
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    Optimal Experimental Design Using a Consistent Bayesian Approach 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:001:;page 11005
    Author(s): Walsh, Scott N.; Wildey, Tim M.; Jakeman, John D.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We consider the utilization of a computational model to guide the optimal acquisition of experimental data to inform the stochastic description of model input parameters. Our formulation is based on the recently developed ...
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