18 citations · 20 across the 8 of their papers we have counts for
5 papers · 1 filter
BOCoDe: Engineering-Centered Benchmarking for Bayesian Optimization
Rosen Ting-Ying Yu, Christophe Hatterer, Advaith Narayanan +2
Bayesian optimization (BO) is a sample-efficient, surrogate-based approach to black-box optimization (BBO), but its evaluation remains dominated by synthetic functions and hyperpar…
GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
Rosen Ting-Ying Yu, Cyril Picard, Faez Ahmed
Bayesian optimization (BO) struggles in high dimensions, where Gaussian-process surrogates demand heavy retraining and brittle assumptions, slowing progress on real engineering and…
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…
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…
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…