6 citations · 11 across the 8 of their papers we have counts for
8 papers
TabPFN for Zero-shot Parametric Engineering Design Generation
Ke Wang, Yifan Tang, Nguyen Gia Hien Vu +2
Deep generative models for engineering design often require substantial computational cost, large training datasets, and extensive retraining when design requirements or datasets c…
FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models
Rosen Ting-Ying Yu, Nicholas Sung, Faez Ahmed
Multi-fidelity (MF) regression often operates in regimes of extreme data imbalance, where the commonly-used Gaussian-process (GP) surrogates struggle with cubic scaling costs and o…
Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Models
Alexander Htet Kyaw, Richa Gupta, Dhruv Shah +8
Advances in 3D generative AI have enabled the creation of physical objects from text prompts, but challenges remain in creating objects involving multiple component types. We prese…
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…
MicroLad: 2D-to-3D Microstructure Reconstruction and Generation via Latent Diffusion and Score Distillation
Kang-Hyun Lee, Faez Ahmed
A major obstacle to establishing reliable structure-property (SP) linkages in materials engineering is the scarcity of diverse 3D microstructure datasets. Limited dataset availabil…
Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study
Kaira M. Samuel, Faez Ahmed
Engineering problems that apply machine learning often involve computationally intensive methods but rely on limited datasets. As engineering data evolves with new designs and cons…
IM-Context: In-Context Learning for Imbalanced Regression Tasks
Ismail Nejjar, Faez Ahmed, Olga Fink
Regression models often fail to generalize effectively in regions characterized by highly imbalanced label distributions. Previous methods for deep imbalanced regression rely on gr…
From Cloud to Edge: Rethinking Generative AI for Low-Resource Design Challenges
Sai Krishna Revanth Vuruma, Ashley Margetts, Jianhai Su +2
Generative Artificial Intelligence (AI) has shown tremendous prospects in all aspects of technology, including design. However, due to its heavy demand on resources, it is usually…