6 papers
LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation
Ghadi Nehme, Yanxia Zhang, Dule Shu +2
Generating high-fidelity 3D geometries under explicit parameter constraints is central to engineering design, yet current methods often require large datasets and fail to provide r…
ShaLa: Multimodal Shared Latent Space Modelling
Jiali Cui, Yan-Ying Chen, Yanxia Zhang +1
This paper presents a novel generative framework for learning shared latent representations across multimodal data. Many advanced multimodal methods focus on capturing all combinat…
Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder
Wonwoong Cho, Yan-Ying Chen, Matthew Klenk +2
Text-to-Image (T2I) Diffusion Models have achieved remarkable performance in generating high quality images. However, enabling precise control of continuous attributes, especially…
ConjointNet: Enhancing Conjoint Analysis for Preference Prediction with Representation Learning
Yanxia Zhang, Francine Chen, Shabnam Hakimi +9
Understanding consumer preferences is essential to product design and predicting market response to these new products. Choice-based conjoint analysis is widely used to model user…
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…