Zobrazeno 1 - 10
of 6 432
pro vyhledávání: '"A. Tailor"'
Autor:
Narayanswamy, Girish, Liu, Xin, Ayush, Kumar, Yang, Yuzhe, Xu, Xuhai, Liao, Shun, Garrison, Jake, Tailor, Shyam, Sunshine, Jake, Liu, Yun, Althoff, Tim, Narayanan, Shrikanth, Kohli, Pushmeet, Zhan, Jiening, Malhotra, Mark, Patel, Shwetak, Abdel-Ghaffar, Samy, McDuff, Daniel
Wearable sensors have become ubiquitous thanks to a variety of health tracking features. The resulting continuous and longitudinal measurements from everyday life generate large volumes of data; however, making sense of these observations for scienti
Externí odkaz:
http://arxiv.org/abs/2410.13638
Autor:
Schwöbel, Pola, Franceschi, Luca, Zafar, Muhammad Bilal, Vasist, Keerthan, Malhotra, Aman, Shenhar, Tomer, Tailor, Pinal, Yilmaz, Pinar, Diamond, Michael, Donini, Michele
fmeval is an open source library to evaluate large language models (LLMs) in a range of tasks. It helps practitioners evaluate their model for task performance and along multiple responsible AI dimensions. This paper presents the library and exposes
Externí odkaz:
http://arxiv.org/abs/2407.12872
Autor:
Bonato, Matteo, Baronchelli, Ivano, Casasola, Viviana, De Zotti, Gianfranco, Trobbiani, Leonardo, Ruli, Erlis, Tailor, Vidhi, Bianchi, Simone
We exploit the DustPedia sample of galaxies within approximately 40 Mpc, selecting 388 sources, to investigate the correlations between IR luminosity (L$_{\rm IR}$), the star formation rate (SFR), and the CO(1-0) luminosity (L$_{\rm CO}$) down to muc
Externí odkaz:
http://arxiv.org/abs/2407.10801
Autor:
Cosentino, Justin, Belyaeva, Anastasiya, Liu, Xin, Furlotte, Nicholas A., Yang, Zhun, Lee, Chace, Schenck, Erik, Patel, Yojan, Cui, Jian, Schneider, Logan Douglas, Bryant, Robby, Gomes, Ryan G., Jiang, Allen, Lee, Roy, Liu, Yun, Perez, Javier, Rogers, Jameson K., Speed, Cathy, Tailor, Shyam, Walker, Megan, Yu, Jeffrey, Althoff, Tim, Heneghan, Conor, Hernandez, John, Malhotra, Mark, Stern, Leor, Matias, Yossi, Corrado, Greg S., Patel, Shwetak, Shetty, Shravya, Zhan, Jiening, Prabhakara, Shruthi, McDuff, Daniel, McLean, Cory Y.
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich, longitudinal data for personal health monitoring. Here we present Pers
Externí odkaz:
http://arxiv.org/abs/2406.06474
Autor:
Merrill, Mike A., Paruchuri, Akshay, Rezaei, Naghmeh, Kovacs, Geza, Perez, Javier, Liu, Yun, Schenck, Erik, Hammerquist, Nova, Sunshine, Jake, Tailor, Shyam, Ayush, Kumar, Su, Hao-Wei, He, Qian, McLean, Cory Y., Malhotra, Mark, Patel, Shwetak, Zhan, Jiening, Althoff, Tim, McDuff, Daniel, Liu, Xin
Despite the proliferation of wearable health trackers and the importance of sleep and exercise to health, deriving actionable personalized insights from wearable data remains a challenge because doing so requires non-trivial open-ended analysis of th
Externí odkaz:
http://arxiv.org/abs/2406.06464
Autor:
Palmiero, Allison, Liu, Kevin, Colnot, Julie, Chopra, Nitish, Neill, Denae, Connell, Luke, Velasquez, Brett, Koong, Albert C., Lin, Steven H., Balter, Peter, Tailor, Ramesh, Robert, Charlotte, Germond, Jean-François, Jorge, Patrik Gonçalves, Geyer, Reiner, Beddar, Sam, Moeckli, Raphael, Schüler, Emil
Background & Purpose: FLASH or ultra-high dose rate (UHDR) radiation therapy (RT) has gained attention in recent years for its ability to spare normal tissues relative to conventional dose rate (CDR) RT in various preclinical trials. However, clinica
Externí odkaz:
http://arxiv.org/abs/2405.15146
Autor:
Tushar, Fakrul Islam, Wang, Avivah, Dahal, Lavsen, Harowicz, Michael R., Lafata, Kyle J., Tailor, Tina D., Lo, Joseph Y.
Lung cancer's high mortality rate can be mitigated by early detection, increasingly reliant on AI for diagnostic imaging. However, AI model performance depends on training and validation datasets. This study develops and validates AI models for both
Externí odkaz:
http://arxiv.org/abs/2405.04605
Autor:
J. Khwaja, J. Bomsztyk, S. Mahmood, B. Wisniowski, R. Shah, A. Tailor, K. Yong, R. Popat, N. Rabin, C. Kyriakou, J. Sive, S. Worthington, A. Hart, E. Dowling, N. Correia, C. Bygrave, A. Rydzewski, K. Jamroziak, A. Wechalekar
Publikováno v:
HemaSphere, Vol 6, Pp 808-809 (2022)
Externí odkaz:
https://doaj.org/article/b494485b154c40b3b219efd0abe75716
Autor:
Spathis, Dimitris, Saeed, Aaqib, Etemad, Ali, Tonekaboni, Sana, Laskaridis, Stefanos, Deldari, Shohreh, Tang, Chi Ian, Schwab, Patrick, Tailor, Shyam
This non-archival index is not complete, as some accepted papers chose to opt-out of inclusion. The list of all accepted papers is available on the workshop website.
Externí odkaz:
http://arxiv.org/abs/2403.10561
The learning to defer (L2D) framework allows autonomous systems to be safe and robust by allocating difficult decisions to a human expert. All existing work on L2D assumes that each expert is well-identified, and if any expert were to change, the sys
Externí odkaz:
http://arxiv.org/abs/2403.02683