| Local latent space Bayesian optimization over structured inputs N Maus, H Jones, J Moore, MJ Kusner, J Bradshaw, J Gardner Advances in neural information processing systems 35, 34505-34518, 2022 | 45 | 2022 |
| Adversarial prompting for black box foundation models N Maus, P Chao, E Wong, J Gardner arXiv preprint arXiv:2302.04237 1 (2), 2023 | 40 | 2023 |
| Black box adversarial prompting for foundation models N Maus, P Chao, E Wong, J Gardner arXiv preprint arXiv:2302.04237, 2023 | 14 | 2023 |
| Gaze-guided magnification for individuals with vision impairments N Maus, D Rutledge, S Al-Khazraji, R Bailey, CO Alm, K Shinohara Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing …, 2020 | 9 | 2020 |
| Discovering many diverse solutions with bayesian optimization N Maus, K Wu, D Eriksson, J Gardner arXiv preprint arXiv:2210.10953, 2022 | 8 | 2022 |
| Classification of high density regions in global ionospheric maps with neural networks O Verkhoglyadova, N Maus, X Meng Earth and Space Science 8 (7), e2021EA001639, 2021 | 3 | 2021 |
| Joint Composite Latent Space Bayesian Optimization N Maus, ZJ Lin, M Balandat, E Bakshy arXiv preprint arXiv:2311.02213, 2023 | 2 | 2023 |
| Inverse Protein Folding Using Deep Bayesian Optimization N Maus, Y Zeng, DA Anderson, P Maffettone, A Solomon, P Greenside, ... arXiv preprint arXiv:2305.18089, 2023 | 1 | 2023 |
| Estimating heading from optic flow: Comparing deep learning network and human performance N Maus, OW Layton Neural Networks 154, 383-396, 2022 | 1 | 2022 |
| Variational Gaussian Processes with Decoupled Conditionals X Zhu, K Wu, N Maus, J Gardner, D Bindel Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Generative modeling for RNA splicing code predictions and design D Wu, A Jha, S Jewell, N Maus, JR Gardner, Y Barash | | 2023 |
| How to identify and understand large-scale structuring in global ionospheric maps? O Verkhoglyadova, X Meng, J Kosberg, N Maus AGU Fall Meeting Abstracts 2021, SA15B-1934, 2021 | | 2021 |
