Nate Gruver
Publications by Year
Research Areas
Machine Learning in Materials Science, Topic Modeling, Protein Structure and Dynamics, Face and Expression Recognition, Natural Language Processing Techniques
Most-Cited Works
- → Large Language Models Are Zero-Shot Time Series Forecasters(2023)94 cited
- → Fine-Tuned Language Models Generate Stable Inorganic Materials as Text(2024)34 cited
- → On Feature Learning in the Presence of Spurious Correlations(2022)23 cited
- → Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders(2022)22 cited
- → Protein Design with Guided Discrete Diffusion(2023)18 cited
- → Deconstructing the Inductive Biases of Hamiltonian Neural Networks(2022)14 cited
- → Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables(2020)10 cited
- → The Lie Derivative for Measuring Learned Equivariance(2022)6 cited
- → Using Latent Variable Models to Observe Academic Pathways(2019)3 cited
- → Adaptive Informative Path Planning with Multimodal Sensing(2020)2 cited