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 | 78 | 2022 |
Adversarial prompting for black box foundation models N Maus, P Chao, E Wong, J Gardner arXiv preprint arXiv:2302.04237 1 (2), 2023 | 58 | 2023 |
Black box adversarial prompting for foundation models N Maus, P Chao, E Wong, J Gardner arXiv preprint arXiv:2302.04237, 2023 | 50 | 2023 |
Discovering many diverse solutions with Bayesian optimization N Maus, K Wu, D Eriksson, J Gardner arXiv preprint arXiv:2210.10953, 2022 | 24 | 2022 |
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 | 12 | 2020 |
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 | 8 | 2021 |
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 | 4 | 2023 |
Estimating heading from optic flow: Comparing deep learning network and human performance N Maus, OW Layton Neural Networks 154, 383-396, 2022 | 3 | 2022 |
Variational gaussian processes with decoupled conditionals X Zhu, K Wu, N Maus, J Gardner, D Bindel Advances in Neural Information Processing Systems 36, 46191-46211, 2023 | 2 | 2023 |
Joint composite latent space bayesian optimization N Maus, ZJ Lin, M Balandat, E Bakshy arXiv preprint arXiv:2311.02213, 2023 | 2 | 2023 |
Approximation-aware bayesian optimization N Maus, K Kim, G Pleiss, D Eriksson, JP Cunningham, JR Gardner arXiv preprint arXiv:2406.04308, 2024 | 1 | 2024 |
A generative artificial intelligence approach for antibiotic optimization MDT Torres, Y Zeng, F Wan, N Maus, J Gardner, C de la Fuente-Nunez bioRxiv, 2024.11. 27.625757, 2024 | 1 | 2024 |
Generative modeling for RNA splicing code predictions and design D Wu, A Jha, S Jewell, N Maus, JR Gardner, Y Barash | 1 | 2023 |
Learned Offline Query Planning via Bayesian Optimization J Tao, N Maus, H Jones, Y Zeng, JR Gardner, R Marcus arXiv preprint arXiv:2502.05256, 2025 | | 2025 |
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization N Maus, K Kim, Y Zeng, HT Jones, F Wan, MDT Torres, ... arXiv preprint arXiv:2501.19342, 2025 | | 2025 |
Generative modeling for RNA splicing predictions and design D Wu, N Maus, A Jha, K Yang, BD Wales-McGrath, S Jewell, A Tangiyan, ... bioRxiv, 2025.01. 20.633986, 2025 | | 2025 |
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 |