Natalie Maus

According to our database, Natalie Maus authored at least 13 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, August, 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, June, 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, March, 2025

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, January, 2025

2024

Approximation-Aware Bayesian Optimization.

Natalie Maus, Kyurae Kim, David Eriksson, Geoff Pleiss, John P. Cunningham, Jacob R. Gardner

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Joint Composite Latent Space Bayesian Optimization.

Natalie Maus, Zhiyuan (Jerry) Lin, Maximilian Balandat, Eytan Bakshy

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Adversarial Prompting for Black Box Foundation Models.

Natalie Maus, Patrick Chao, Eric Wong, Jacob R. Gardner

CoRR, 2023

Variational Gaussian Processes with Decoupled Conditionals.

Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob R. Gardner, David Bindel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discovering Many Diverse Solutions with Bayesian Optimization.

Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Estimating heading from optic flow: Comparing deep learning network and human performance.

Natalie Maus, Oliver W. Layton

Neural Networks, 2022

Local Latent Space Bayesian Optimization over Structured Inputs.

Natalie Maus, Haydn Thomas Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Gaze-guided Magnification for Individuals with Vision Impairments.

Natalie Maus, Dalton Rutledge, Sedeeq Al-khazraji, Reynold Bailey, Cecilia Ovesdotter Alm, Kristen Shinohara

Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020