PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

Understand

Engineering design tasks often require synthesizing new designs that meet desired performance requirements.

• The conventional design process, which requires iterative optimization and performance evaluation, is slow and dependent on initial designs.
• Past work has used conditional generative adversarial networks (cGANs) to enable direct design synthesis for given target performances.
• However, most existing cGANs are restricted to categorical conditions.