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    Deep Generative Models in Engineering Design: A Review 

    Source: Journal of Mechanical Design:;2022:;volume( 144 ):;issue: 007:;page 71704
    Author(s): Regenwetter, Lyle;Nobari, Amin Heyrani;Ahmed, Faez
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Automated design synthesis has the potential to revolutionize the modern engineering design process and improve access to highly optimized and customized products across countless industries. Successfully adapting generative ...
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    Range-Constrained Generative Adversarial Network: Design Synthesis Under Constraints Using Conditional Generative Adversarial Networks 

    Source: Journal of Mechanical Design:;2021:;volume( 144 ):;issue: 002:;page 21708-1
    Author(s): Nobari, Amin Heyrani; Chen, Wei; Ahmed, Faez
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Typical engineering design tasks require the effort to modify designs iteratively until they meet certain constraints, i.e., performance or attribute requirements. Past work has proposed ways to solve the inverse design ...
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