5 papers · 1 filter
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…
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…
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.…