28 citations · 40 across the 11 of their papers we have counts for
5 papers · 1 filter
Stylish and Functional: Guided Interpolation Subject to Physical Constraints
Yan-Ying Chen, Nikos Arechiga, Chenyang Yuan +3
Generative AI is revolutionizing engineering design practices by enabling rapid prototyping and manipulation of designs. One example of design manipulation involves taking two refe…
Parametric-ControlNet: Multimodal Control in Foundation Models for Precise Engineering Design Synthesis
Rui Zhou, Yanxia Zhang, Chenyang Yuan +4
This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engi…
Enhancing Sample Generation of Diffusion Models using Noise Level Correction
Abulikemu Abuduweili, Chenyang Yuan, Changliu Liu +1
The denoising process of diffusion models can be interpreted as an approximate projection of noisy samples onto the data manifold. Moreover, the noise level in these samples approx…
VehicleSDF: A 3D generative model for constrained engineering design via surrogate modeling
Hayata Morita, Kohei Shintani, Chenyang Yuan +1
A main challenge in mechanical design is to efficiently explore the design space while satisfying engineering constraints. This work explores the use of 3D generative models to exp…
Bridging Design Gaps: A Parametric Data Completion Approach With Graph Guided Diffusion Models
Rui Zhou, Chenyang Yuan, Frank Permenter +4
This study introduces a generative imputation model leveraging graph attention networks and tabular diffusion models for completing missing parametric data in engineering designs.…