activity
20222024
most citedDiffusion Models Beat GANs on Topology Optimization

22 citations · 53 across the 16 of their papers we have counts for

collaborators

18 papers

cs.AI20242 cited

CAD-Prompted Generative Models: A Pathway to Feasible and Novel Engineering Designs

Leah Chong, Jude Rayan, Steven Dow +2

Text-to-image generative models have increasingly been used to assist designers during concept generation in various creative domains, such as graphic design, user interface design…

eess.SY2024

C-ShipGen: A Conditional Guided Diffusion Model for Parametric Ship Hull Design

Noah J. Bagazinski, Faez Ahmed

Ship design is a complex design process that may take a team of naval architects many years to complete. Improving the ship design process can lead to significant cost savings, whi…

cs.CE2024

Fast and Accurate Bayesian Optimization with Pre-trained Transformers for Constrained Engineering Problems

Rosen, Yu, Cyril Picard +1

Bayesian Optimization (BO) is a foundational strategy in the field of engineering design optimization for efficiently handling black-box functions with many constraints and expensi…

cs.AI20246 cited

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…

cs.CV20241 cited

BIKED++: A Multimodal Dataset of 1.4 Million Bicycle Image and Parametric CAD Designs

Lyle Regenwetter, Yazan Abu Obaideh, Amin Heyrani Nobari +1

This paper introduces a public dataset of 1.4 million procedurally-generated bicycle designs represented parametrically, as JSON files, and as rasterized images. The dataset is cre…

cs.LG20241 cited

NITO: Neural Implicit Fields for Resolution-free Topology Optimization

Amin Heyrani Nobari, Giorgio Giannone, Lyle Regenwetter +1

Topology optimization is a critical task in engineering design, where the goal is to optimally distribute material in a given space for maximum performance. We introduce Neural Imp…