Nate Gruver

According to our database, Nate Gruver authored at least 12 papers between 2018 and 2024.

Collaborative distances:

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

2024

Large Language Models Must Be Taught to Know What They Don't Know.

Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson

CoRR, 2024

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text.

Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Protein Design with Guided Discrete Diffusion.

Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson

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

Large Language Models Are Zero-Shot Time Series Forecasters.

Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson

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

The Lie Derivative for Measuring Learned Equivariance.

Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

On Feature Learning in the Presence of Spurious Correlations.

Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson

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

Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders.

Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson

Proceedings of the International Conference on Machine Learning, 2022

Deconstructing the Inductive Biases of Hamiltonian Neural Networks.

Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables.

Nate Gruver, Jiaming Song, Mykel J. Kochenderfer, Stefano Ermon

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Adaptive Informative Path Planning with Multimodal Sensing.

Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer

Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, 2020

2019

Using Latent Variable Models to Observe Academic Pathways.

Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke

Proceedings of the 12th International Conference on Educational Data Mining, 2019

2018

Amanuensis: The Programmer's Apprentice.

Thomas Dean, Maurice Chiang, Marcus Gomez, Nate Gruver, Yousef Hindy, Michelle Lam, Peter Lu, Sophia Sanchez, Rohun Saxena, Michael Smith, Lucy Wang, Catherine Wong

CoRR, 2018