18 citations · 25 across the 14 of their papers we have counts for
6 papers · 1 filter
Generative Optimization: A Perspective on AI-Enhanced Problem Solving in Engineering
Lyle Regenwetter, Cyril Picard, Amin Heyrani Nobari +2
The field of engineering is shaped by the tools and methods used to solve problems. Optimization is one such class of powerful, robust, and effective engineering tools proven over…
LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis
Amin Heyrani Nobari, Akash Srivastava, Dan Gutfreund +2
In this paper, we introduce LInK, a novel framework that integrates contrastive learning of performance and design space with optimization techniques for solving complex inverse pr…
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…
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…
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…
Fast and Accurate Zero-Training Classification for Tabular Engineering Data
Cyril Picard, Faez Ahmed
In engineering design, navigating complex decision-making landscapes demands a thorough exploration of the design, performance, and constraint spaces, often impeded by resource-int…