Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ahdritz, Gustaf"'
Chatbots built upon language models have exploded in popularity, but they have largely been limited to synchronous, turn-by-turn dialogues. In this paper we present a simple yet general method to simulate real-time interactive conversations using pre
Externí odkaz:
http://arxiv.org/abs/2405.13203
We study the feasibility of identifying epistemic uncertainty (reflecting a lack of knowledge), as opposed to aleatoric uncertainty (reflecting entropy in the underlying distribution), in the outputs of large language models (LLMs) over free-form tex
Externí odkaz:
http://arxiv.org/abs/2402.03563
Autor:
Song, Shuaiwen Leon, Kruft, Bonnie, Zhang, Minjia, Li, Conglong, Chen, Shiyang, Zhang, Chengming, Tanaka, Masahiro, Wu, Xiaoxia, Rasley, Jeff, Awan, Ammar Ahmad, Holmes, Connor, Cai, Martin, Ghanem, Adam, Zhou, Zhongzhu, He, Yuxiong, Luferenko, Pete, Kumar, Divya, Weyn, Jonathan, Zhang, Ruixiong, Klocek, Sylwester, Vragov, Volodymyr, AlQuraishi, Mohammed, Ahdritz, Gustaf, Floristean, Christina, Negri, Cristina, Kotamarthi, Rao, Vishwanath, Venkatram, Ramanathan, Arvind, Foreman, Sam, Hippe, Kyle, Arcomano, Troy, Maulik, Romit, Zvyagin, Maxim, Brace, Alexander, Zhang, Bin, Bohorquez, Cindy Orozco, Clyde, Austin, Kale, Bharat, Perez-Rivera, Danilo, Ma, Heng, Mann, Carla M., Irvin, Michael, Pauloski, J. Gregory, Ward, Logan, Hayot, Valerie, Emani, Murali, Xie, Zhen, Lin, Diangen, Shukla, Maulik, Foster, Ian, Davis, James J., Papka, Michael E., Brettin, Thomas, Balaprakash, Prasanna, Tourassi, Gina, Gounley, John, Hanson, Heidi, Potok, Thomas E, Pasini, Massimiliano Lupo, Evans, Kate, Lu, Dan, Lunga, Dalton, Yin, Junqi, Dash, Sajal, Wang, Feiyi, Shankar, Mallikarjun, Lyngaas, Isaac, Wang, Xiao, Cong, Guojing, Zhang, Pei, Fan, Ming, Liu, Siyan, Hoisie, Adolfy, Yoo, Shinjae, Ren, Yihui, Tang, William, Felker, Kyle, Svyatkovskiy, Alexey, Liu, Hang, Aji, Ashwin, Dalton, Angela, Schulte, Michael, Schulz, Karl, Deng, Yuntian, Nie, Weili, Romero, Josh, Dallago, Christian, Vahdat, Arash, Xiao, Chaowei, Gibbs, Thomas, Anandkumar, Anima, Stevens, Rick
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scientific exploration, bringing significant advancements across sectors fro
Externí odkaz:
http://arxiv.org/abs/2310.04610
Autor:
Ahdritz, Gustaf, Bouatta, Nazim, Kadyan, Sachin, Jarosch, Lukas, Berenberg, Daniel, Fisk, Ian, Watkins, Andrew M., Ra, Stephen, Bonneau, Richard, AlQuraishi, Mohammed
Multiple sequence alignments (MSAs) of proteins encode rich biological information and have been workhorses in bioinformatic methods for tasks like protein design and protein structure prediction for decades. Recent breakthroughs like AlphaFold2 that
Externí odkaz:
http://arxiv.org/abs/2308.05326
Akademický článek
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Akademický článek
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Autor:
Chowdhury, Ratul, Bouatta, Nazim, Biswas, Surojit, Floristean, Christina, Kharkar, Anant, Roy, Koushik, Rochereau, Charlotte, Ahdritz, Gustaf, Zhang, Joanna, Church, George M., Sorger, Peter K., AlQuraishi, Mohammed
Publikováno v:
Nature Biotechnology; Nov2022, Vol. 40 Issue 11, p1692-1692, 1p
Autor:
Ahdritz G; Harvard University., Bouatta N; Laboratory of Systems Pharmacology, Harvard Medical School., Kadyan S; Columbia University., Jarosch L; Columbia University., Berenberg D; Prescient Design, Genentech & Department of Computer Science, New York University., Fisk I; Flatiron Institute., Watkins AM; Prescient Design, Genentech., Ra S; Prescient Design, Genentech., Bonneau R; Prescient Design, Genentech., AlQuraishi M; Department of Systems Biology, Columbia University.
Publikováno v:
ArXiv [ArXiv] 2023 Aug 10. Date of Electronic Publication: 2023 Aug 10.