4 papers
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim, Jiayao Gu, Ye Yuan +4
Offline optimization is a fundamental challenge in science and engineering, where the goal is to optimize black-box functions using only offline datasets. This setting is particula…
Robust Guided Diffusion for Offline Black-Box Optimization
Can Sam Chen, Christopher Beckham, Zixuan Liu +2
Offline black-box optimization aims to maximize a black-box function using an offline dataset of designs and their measured properties. Two main approaches have emerged: the forwar…
Importance-aware Co-teaching for Offline Model-based Optimization
Ye Yuan, Can Chen, Zixuan Liu +2
Offline model-based optimization aims to find a design that maximizes a property of interest using only an offline dataset, with applications in robot, protein, and molecule design…
Parallel-mentoring for Offline Model-based Optimization
Can Chen, Christopher Beckham, Zixuan Liu +2
We study offline model-based optimization to maximize a black-box objective function with a static dataset of designs and scores. These designs encompass a variety of domains, incl…