4 papers
Much Ado About Noising: Dispelling the Myths of Generative Robotic Control
Chaoyi Pan, Giri Anantharaman, Nai-Chieh Huang +8
Generative models, like flows and diffusions, have recently emerged as popular and efficacious policy parameterizations in robotics. There has been much speculation as to the facto…
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…