13 citations · 34 across the 13 of their papers we have counts for
3 papers · 1 filter
Joint Composite Latent Space Bayesian Optimization
Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat +1
Bayesian Optimization (BO) is a technique for sample-efficient black-box optimization that employs probabilistic models to identify promising input locations for evaluation. When d…
Inverse Protein Folding Using Deep Bayesian Optimization
Natalie Maus, Yimeng Zeng, Daniel Allen Anderson +5
Inverse protein folding -- the task of predicting a protein sequence from its backbone atom coordinates -- has surfaced as an important problem in the "top down", de novo design of…
Black Box Adversarial Prompting for Foundation Models
Natalie Maus, Patrick Chao, Eric Wong +1
Prompting interfaces allow users to quickly adjust the output of generative models in both vision and language. However, small changes and design choices in the prompt can lead to…