Gaze-guided Magnification for Individuals with Vision Impairments. - Natalie Maus; Dalton Rutledge; Sedeeq Al-khazraji; Reynold Bailey; Cecilia Ovesdotter Alm; Kristen Shinohara (CHI Extended Abstracts, 2020)

Local Latent Space Bayesian Optimization over Structured Inputs. - Natalie Maus; Haydn Thomas Jones; Juston Moore; Matt J. Kusner; John Bradshaw; Jacob R. Gardner (NeurIPS, 2022)

Estimating heading from optic flow: Comparing deep learning network and human performance. - Natalie Maus; Oliver W. Layton (Neural Networks, 2022)

Discovering Many Diverse Solutions with Bayesian Optimization. - Natalie Maus; Kaiwen Wu; David Eriksson; Jacob R. Gardner (AISTATS, 2023)

Variational Gaussian Processes with Decoupled Conditionals. - Xinran Zhu; Kaiwen Wu; Natalie Maus; Jacob R. Gardner; David Bindel (NeurIPS, 2023)

Adversarial Prompting for Black Box Foundation Models. - Natalie Maus; Patrick Chao; Eric Wong 001; Jacob R. Gardner (CoRR, 2023)

Inverse Protein Folding Using Deep Bayesian Optimization. - Natalie Maus; Yimeng Zeng; Daniel Allen Anderson; Phillip M. Maffettone; Aaron Solomon; Peyton Greenside; Osbert Bastani; Jacob R. Gardner (CoRR, 2023)

Joint Composite Latent Space Bayesian Optimization. - Natalie Maus; Zhiyuan (Jerry) Lin; Maximilian Balandat; Eytan Bakshy (ICML, 2024)

Approximation-Aware Bayesian Optimization. - Natalie Maus; Kyurae Kim; David Eriksson; Geoff Pleiss; John P. Cunningham; Jacob R. Gardner (NeurIPS, 2024)

Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization. - Natalie Maus; Kyurae Kim; Yimeng Zeng; Haydn Thomas Jones; Fangping Wan; Marcelo Der Torossian Torres; Cesar de la Fuente-Nunez; Jacob R. Gardner (CoRR, 2025)

Large Scale Multi-Task Bayesian Optimization with Large Language Models. - Yimeng Zeng; Natalie Maus; Haydn Thomas Jones; Jeffrey Tao; Fangping Wan; Marcelo Der Torossian Torres; Cesar de la Fuente-Nunez; Ryan Marcus; Osbert Bastani; Jacob R. Gardner (CoRR, 2025)

Learned Offline Query Planning via Bayesian Optimization. - Jeffrey Tao; Natalie Maus; Haydn Thomas Jones; Yimeng Zeng; Jacob R. Gardner; Ryan Marcus (Proc. ACM Manag. Data, 2025)

A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design. - Haydn Thomas Jones; Natalie Maus; Josh Magnus Ludan; Maggie Ziyu Huan; Jiaming Liang; Marcelo Der Torossian Torres; Jiatao Liang; Zachary G. Ives; Yoseph Barash; Cesar de la Fuente-Nunez; Jacob R. Gardner; Mark Yatskar (CoRR, 2025)