Zobrazeno 1 - 10
of 540
pro vyhledávání: '"P, Gruver"'
Autor:
Amin, Alan Nawzad, Gruver, Nate, Kuang, Yilun, Li, Lily, Elliott, Hunter, McCarter, Calvin, Raghu, Aniruddh, Greenside, Peyton, Wilson, Andrew Gordon
To build effective therapeutics, biologists iteratively mutate antibody sequences to improve binding and stability. Proposed mutations can be informed by previous measurements or by learning from large antibody databases to predict only typical antib
Externí odkaz:
http://arxiv.org/abs/2412.07763
Autor:
Kapoor, Sanyam, Gruver, Nate, Roberts, Manley, Collins, Katherine, Pal, Arka, Bhatt, Umang, Weller, Adrian, Dooley, Samuel, Goldblum, Micah, Wilson, Andrew Gordon
When using large language models (LLMs) in high-stakes applications, we need to know when we can trust their predictions. Some works argue that prompting high-performance LLMs is sufficient to produce calibrated uncertainties, while others introduce
Externí odkaz:
http://arxiv.org/abs/2406.08391
Autor:
Gruver, Nate, Sriram, Anuroop, Madotto, Andrea, Wilson, Andrew Gordon, Zitnick, C. Lawrence, Ulissi, Zachary
We propose fine-tuning large language models for generation of stable materials. While unorthodox, fine-tuning large language models on text-encoded atomistic data is simple to implement yet reliable, with around 90% of sampled structures obeying phy
Externí odkaz:
http://arxiv.org/abs/2402.04379
By encoding time series as a string of numerical digits, we can frame time series forecasting as next-token prediction in text. Developing this approach, we find that large language models (LLMs) such as GPT-3 and LLaMA-2 can surprisingly zero-shot e
Externí odkaz:
http://arxiv.org/abs/2310.07820
Autor:
Michael Griffin, Aaron M. Gruver, Chintan Shah, Qasim Wani, Darren Fahy, Archit Khosla, Christian Kirkup, Daniel Borders, Jacqueline A. Brosnan-Cashman, Angie D. Fulford, Kelly M. Credille, Christina Jayson, Fedaa Najdawi, Klaus Gottlieb
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Histological assessment is essential for the diagnosis and management of celiac disease. Current scoring systems, including modified Marsh (Marsh–Oberhuber) score, lack inter-pathologist agreement. To address this unmet need, we aimed to d
Externí odkaz:
https://doaj.org/article/c6797331dcd94b2584d46f440ddf3220
Autor:
Gruver, Nate, Stanton, Samuel, Frey, Nathan C., Rudner, Tim G. J., Hotzel, Isidro, Lafrance-Vanasse, Julien, Rajpal, Arvind, Cho, Kyunghyun, Wilson, Andrew Gordon
Publikováno v:
Advances in Neural Information Processing Systems 36, December 10-16, 2023
A popular approach to protein design is to combine a generative model with a discriminative model for conditional sampling. The generative model samples plausible sequences while the discriminative model guides a search for sequences with high fitnes
Externí odkaz:
http://arxiv.org/abs/2305.20009
Autor:
Kim M. Gruver, Jenny W. Y. Jiao, Eviatar Fields, Sen Song, Per Jesper Sjöström, Alanna J. Watt
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract The spatial organization of a neuronal circuit is critically important for its function since the location of neurons is often associated with function. In the cerebellum, the major output of the cerebellar cortex are synapses made from Purk
Externí odkaz:
https://doaj.org/article/e0641c4a888c44acb4f465cbe04be233
Publikováno v:
Journal of Agriculture, Food Systems, and Community Development, Vol 14, Iss 1 (2024)
Despite being a world-class tourist destination, the U.S. Virgin Islands (USVI—St. Thomas, St. Croix, and St. John) face significant challenges related to diversified crop production, food distribution, and food security. High poverty rates among i
Externí odkaz:
https://doaj.org/article/0290e55300504d35b666d7f4d4e1cbdd
Deep classifiers are known to rely on spurious features $\unicode{x2013}$ patterns which are correlated with the target on the training data but not inherently relevant to the learning problem, such as the image backgrounds when classifying the foreg
Externí odkaz:
http://arxiv.org/abs/2210.11369
Equivariance guarantees that a model's predictions capture key symmetries in data. When an image is translated or rotated, an equivariant model's representation of that image will translate or rotate accordingly. The success of convolutional neural n
Externí odkaz:
http://arxiv.org/abs/2210.02984