Nate Gruver

27 papers A* 10A 1B 1Journal 15
YearRankTypeTitle / Venue / Authors
2025 A* conf
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences.
ICLR
Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson
2025 J jnl
Pearl: A Foundation Model for Placing Every Atom in the Right Location.
CoRR
Alejandro Dobles, Nina Jovic, Kenneth Leidal, Pranav Murugan, David C. Williams, Drausin Wulsin, Nate Gruver, Christina X. Ji, Korrawat Pruegsanusak, Gianluca Scarpellini, Ansh Sharma, Wojciech Swiderski, Andrea Bootsma, Richard Strong Bowen, Charlotte Chen, Jamin Chen, Marc André Dämgen, Benjamin DiFrancesco, J. D. Fishman, Alla Ivanova, Zach Kagin, David Li-Bland, Zuli Liu, Igor Morozov, Jeffrey Ouyang-Zhang, Frank C. Pickard IV, Kushal S. Shah, Ben Shor, Gabriel Monteiro da Silva, Roy Tal, Maxx H. Tessmer, Carl Tilbury, Cyr Vetcher, Daniel Zeng, Maruan Al-Shedivat, Aleksandra Faust, Evan N. Feinberg, Michael V. LeVine, Matteus Pan
2025 J jnl
Triangle Multiplication Is All You Need For Biomolecular Structure Representations.
CoRR
Jeffrey Ouyang-Zhang, Pranav Murugan, Daniel Jesus Diaz, Gianluca Scarpellini, Richard Strong Bowen, Nate Gruver, Adam R. Klivans, Philipp Krähenbühl, Aleksandra Faust, Maruan Al-Shedivat
2025 J jnl
Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion.
CoRR
Alan Nawzad Amin, Nate Gruver, Andrew Gordon Wilson
2024 J jnl
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences.
CoRR
Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson
2024 A* conf
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text.
ICLR
Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi
2024 J jnl
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text.
CoRR
Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi
2024 A* conf
Large Language Models Must Be Taught to Know What They Don't Know.
NeurIPS
Sanyam Kapoor, Nate Gruver, Manley Roberts, Katie Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2024 J jnl
Large Language Models Must Be Taught to Know What They Don't Know.
CoRR
Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2023 A* conf
Large Language Models Are Zero-Shot Time Series Forecasters.
NeurIPS
Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson
2023 J jnl
Large Language Models Are Zero-Shot Time Series Forecasters.
CoRR
Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson
2023 A* conf
Protein Design with Guided Discrete Diffusion.
NeurIPS
Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson
2023 J jnl
Protein Design with Guided Discrete Diffusion.
CoRR
Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson
2023 A* conf
The Lie Derivative for Measuring Learned Equivariance.
ICLR
Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson
2022 A* conf
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders.
ICML
Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson
2022 J jnl
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders.
CoRR
Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson
2022 A* conf
Deconstructing the Inductive Biases of Hamiltonian Neural Networks.
ICLR
Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson
2022 J jnl
Deconstructing the Inductive Biases of Hamiltonian Neural Networks.
CoRR
Nate Gruver, Marc Finzi, Samuel Stanton, Andrew Gordon Wilson
2022 A* conf
On Feature Learning in the Presence of Spurious Correlations.
NeurIPS
Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson
2022 J jnl
On Feature Learning in the Presence of Spurious Correlations.
CoRR
Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson
2022 J jnl
The Lie Derivative for Measuring Learned Equivariance.
CoRR
Nate Gruver, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson
2020 A* conf
Adaptive Informative Path Planning with Multimodal Sensing.
ICAPS
Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer
2020 J jnl
Adaptive Informative Path Planning with Multimodal Sensing.
CoRR
Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer
2020 A conf
Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables.
AAMAS
Nate Gruver, Jiaming Song, Mykel J. Kochenderfer, Stefano Ermon
2019 B conf
Using Latent Variable Models to Observe Academic Pathways.
EDM
Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke
2019 J jnl
Using Latent Variable Models to Observe Academic Pathways.
CoRR
Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke
2018 J jnl
Amanuensis: The Programmer's Apprentice.
CoRR
Thomas Dean, Maurice Chiang, Marcus Gomez, Nate Gruver, Yousef Hindy, Michelle S. Lam, Peter Lu, Sophia Sanchez, Rohun Saxena, Michael Smith, Lucy Wang, Catherine Wong