98 citations · 146 across the 7 of their papers we have counts for
6 papers
Deep Generative Models for Geometric Design Under Uncertainty
Wei Wayne Chen, Doksoo Lee, Wei Chen
Deep generative models have demonstrated effectiveness in learning compact and expressive design representations that significantly improve geometric design optimization. However,…
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
Amin Heyrani Nobari, Wei Chen, Faez Ahmed
Engineering design tasks often require synthesizing new designs that meet desired performance requirements. The conventional design process, which requires iterative optimization a…
Range-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis
Amin Heyrani Nobari, Wei Chen, Faez Ahmed
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 pr…
IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures
Jun Wang, Wei Wayne Chen, Daicong Da +2
Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete densit…
Deep Generative Model for Efficient 3D Airfoil Parameterization and Generation
Wei Chen, Arun Ramamurthy
In aerodynamic shape optimization, the convergence and computational cost are greatly affected by the representation capacity and compactness of the design space. Previous research…
Adaptive Expansion Bayesian Optimization for Unbounded Global Optimization
Wei Chen, Mark Fuge
Bayesian optimization is normally performed within fixed variable bounds. In cases like hyperparameter tuning for machine learning algorithms, setting the variable bounds is not tr…