Maus, Natalie

8 publications

NeurIPS 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 Ives, Yoseph Barash, Cesar de la Fuente-Nunez, Jacob R. Gardner, Mark Yatskar

NeurIPS 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

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

ICML 2024 Joint Composite Latent Space Bayesian Optimization Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat, Eytan Bakshy

ICMLW 2023 Black Box Adversarial Prompting for Foundation Models Natalie Maus, Patrick Chao, Eric Wong, Jacob R. Gardner

AISTATS 2023 Discovering Many Diverse Solutions with Bayesian Optimization Natalie Maus, Kaiwen Wu, David Eriksson, Jacob Gardner

NeurIPS 2023 Variational Gaussian Processes with Decoupled Conditionals Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob Gardner, David Bindel

NeurIPS 2022 Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus, Haydn Jones, Juston Moore, Matt J Kusner, John Bradshaw, Jacob Gardner