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