no code implementations • 13 Feb 2024 • Muhammad Usama, Zahid Masood, Shahroz Khan, Konstantinos Kostas, Panagiotis Kaklis
In this work, we perform a systematic comparison of the effectiveness and efficiency of generative and non-generative models in constructing design spaces for novel and efficient design exploration and shape optimization.
no code implementations • 29 Apr 2023 • Shahroz Khan, Kosa Goucher-Lambert, Konstantinos Kostas, Panagiotis Kaklis
In this work, we introduce ShipHullGAN, a generic parametric modeller built using deep convolutional generative adversarial networks (GANs) for the versatile representation and generation of ship hulls.