| On feature learning in the presence of spurious correlations P Izmailov, P Kirichenko, N Gruver, AG Wilson Advances in Neural Information Processing Systems 35, 38516-38532, 2022 | 68 | 2022 |
| Large language models are zero-shot time series forecasters N Gruver, M Finzi, S Qiu, AG Wilson Advances in Neural Information Processing Systems, 2023 | 61 | 2023 |
| Accelerating bayesian optimization for biological sequence design with denoising autoencoders S Stanton, W Maddox, N Gruver, P Maffettone, E Delaney, P Greenside, ... International Conference on Machine Learning, 20459-20478, 2022 | 53 | 2022 |
| Deconstructing the Inductive Biases of Hamiltonian Neural Networks N Gruver, M Finzi, S Stanton, AG Wilson International Conference on Learning Representations, 2022 | 39 | 2022 |
| Protein Design with Guided Discrete Diffusion N Gruver, S Stanton, NC Frey, TGJ Rudner, I Hotzel, J Lafrance-Vanasse, ... Advances in Neural Information Processing Systems, 2023 | 25 | 2023 |
| The lie derivative for measuring learned equivariance N Gruver, M Finzi, M Goldblum, AG Wilson International Conference on Learning Representations, 2023 | 23 | 2023 |
| Multi-agent adversarial inverse reinforcement learning with latent variables N Gruver, J Song, MJ Kochenderfer, S Ermon Proceedings of the 19th International Conference on Autonomous Agents and …, 2020 | 19 | 2020 |
| Adaptive informative path planning with multimodal sensing S Choudhury, N Gruver, MJ Kochenderfer Proceedings of the International Conference on Automated Planning and …, 2020 | 17 | 2020 |
| Effective Surrogate Models for Protein Design with Bayesian Optimization N Gruver, S Stanton, P Kirichenko, M Finzi, P Maffettone, V Myers, ... ICML Workshop on Computational Biology, 2021 | 13 | 2021 |
| Using latent variable models to observe academic pathways N Gruver, A Malik, B Capoor, C Piech, ML Stevens, A Paepcke International Conference on Educational Data Mining, 2019 | 8 | 2019 |
| Fine-Tuned Language Models Generate Stable Inorganic Materials as Text N Gruver, A Sriram, A Madotto, AG Wilson, CL Zitnick, Z Ulissi arXiv preprint arXiv:2402.04379, 2024 | 3 | 2024 |
| Calibration-Tuning: Teaching Large Language Models to Know What They Don’t Know S Kapoor, N Gruver, M Roberts, A Pal, S Dooley, M Goldblum, A Wilson Proceedings of the 1st Workshop on Uncertainty-Aware NLP (UncertaiNLP 2024 …, 2024 | | 2024 |
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
