GUST combines synthetic-data pretraining with transfer learning on a conditional diffusion model to quantify free-form geometric uncertainty in manufactured metamaterials from small real-world datasets.
GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty
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GUST: Quantifying Free-Form Geometric Uncertainty of Metamaterials Using Small Data
GUST combines synthetic-data pretraining with transfer learning on a conditional diffusion model to quantify free-form geometric uncertainty in manufactured metamaterials from small real-world datasets.