Natalie Maus - RankMe

21 papers A* 4A 1Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adversarial Query Synthesis via Bayesian Optimization. CoRR Jeffrey Tao, Yimeng Zeng, Haydn Thomas Jones, Natalie Maus, Osbert Bastani, Jacob R. Gardner, Ryan Marcus
2026	J	`jnl`	Purely Agentic Black-Box Optimization for Biological Design. CoRR Natalie Maus, Yimeng Zeng, Haydn Thomas Jones, Yining Huang, Gaurav Ng Goel, Alden Rose, Kyurae Kim, Hyun-Su Lee, Marcelo Der Torossian Torres, Fangping Wan, Cesar de la Fuente-Nunez, Mark Yatskar, Osbert Bastani, Jacob R. Gardner
2025	J	`jnl`	A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design. CoRR 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
2025	J	`jnl`	Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization. CoRR Natalie Maus, Kyurae Kim, Yimeng Zeng, Haydn Thomas Jones, Fangping Wan, Marcelo Der Torossian Torres, Cesar de la Fuente-Nunez, Jacob R. Gardner
2025	J	`jnl`	Large Scale Multi-Task Bayesian Optimization with Large Language Models. CoRR 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
2025	J	`jnl`	Learned Offline Query Planning via Bayesian Optimization. CoRR Jeffrey Tao, Natalie Maus, Haydn Thomas Jones, Yimeng Zeng, Jacob R. Gardner, Ryan Marcus
2025	J	`jnl`	Learned Offline Query Planning via Bayesian Optimization. Proc. ACM Manag. Data Jeffrey Tao, Natalie Maus, Haydn Thomas Jones, Yimeng Zeng, Jacob R. Gardner, Ryan Marcus
2025	J	`jnl`	We Still Don't Understand High-Dimensional Bayesian Optimization. CoRR Colin Doumont, Donney Fan, Natalie Maus, Jacob R. Gardner, Henry B. Moss, Geoff Pleiss
2024	A*	`conf`	Approximation-Aware Bayesian Optimization. NeurIPS Natalie Maus, Kyurae Kim, David Eriksson, Geoff Pleiss, John P. Cunningham, Jacob R. Gardner
2024	J	`jnl`	Approximation-Aware Bayesian Optimization. CoRR Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner
2024	A*	`conf`	Joint Composite Latent Space Bayesian Optimization. ICML Natalie Maus, Zhiyuan (Jerry) Lin, Maximilian Balandat, Eytan Bakshy
2023	J	`jnl`	Adversarial Prompting for Black Box Foundation Models. CoRR Natalie Maus, Patrick Chao, Eric Wong, Jacob R. Gardner
2023	A	`conf`	Discovering Many Diverse Solutions with Bayesian Optimization. AISTATS Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
2023	J	`jnl`	Inverse Protein Folding Using Deep Bayesian Optimization. CoRR Natalie Maus, Yimeng Zeng, Daniel Allen Anderson, Phillip M. Maffettone, Aaron Solomon, Peyton Greenside, Osbert Bastani, Jacob R. Gardner
2023	J	`jnl`	Joint Composite Latent Space Bayesian Optimization. CoRR Natalie Maus, Zhiyuan (Jerry) Lin, Maximilian Balandat, Eytan Bakshy
2023	A*	`conf`	Variational Gaussian Processes with Decoupled Conditionals. NeurIPS Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob R. Gardner, David Bindel
2022	J	`jnl`	Discovering Many Diverse Solutions with Bayesian Optimization. CoRR Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
2022	J	`jnl`	Estimating heading from optic flow: Comparing deep learning network and human performance. Neural Networks Natalie Maus, Oliver W. Layton
2022	A*	`conf`	Local Latent Space Bayesian Optimization over Structured Inputs. NeurIPS Natalie Maus, Haydn Thomas Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner
2022	J	`jnl`	Local Latent Space Bayesian Optimization over Structured Inputs. CoRR Natalie Maus, Haydn Thomas Jones, Juston S. Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner
2020	—	`conf`	Gaze-guided Magnification for Individuals with Vision Impairments. CHI Extended Abstracts Natalie Maus, Dalton Rutledge, Sedeeq Al-khazraji, Reynold Bailey, Cecilia Ovesdotter Alm, Kristen Shinohara