Positive and Unlabeled Data: Model, Estimation, Inference, and Classification

Autor: Liu, Siyan, Yeh, Chi-Kuang, Zhang, Xin, Tian, Qinglong, Li, Pengfei

This study introduces a new approach to addressing positive and unlabeled (PU) data through the double exponential tilting model (DETM). Traditional methods often fall short because they only apply to selected completely at random (SCAR) PU data, whe

Externí odkaz: http://arxiv.org/abs/2407.09735

Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier

Autor: Tsaris, Aristeidis, Zhang, Chengming, Wang, Xiao, Yin, Junqi, Liu, Siyan, Ashfaq, Moetasim, Fan, Ming, Choi, Jong Youl, Wahib, Mohamed, Lu, Dan, Balaprakash, Prasanna, Wang, Feiyi

Vision Transformers (ViTs) are pivotal for foundational models in scientific imagery, including Earth science applications, due to their capability to process large sequence lengths. While transformers for text has inspired scaling sequence lengths i

Externí odkaz: http://arxiv.org/abs/2405.15780

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

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

The lack of causal link between myopia and intraocular pressure: Insights from cross-sectional analysis and Mendelian randomization study

Autor: Deng, Bo, Zhou, Mo, Kong, Xiangmei, Cao, Yang, Tian, Min, Zhou, Qi, Luo, Linbi, Liu, Siyan, Cheng, Zixuan, Lv, Hongbin

Publikováno v: In Photodiagnosis and Photodynamic Therapy October 2024 49

Typical emerging contaminants in sewage treatment plant effluent, and related watersheds in the Pearl River Basin: Ecological risks and source identification

Autor: Zhu, Xiaohui, Liu, Siyan, Gao, Xiaofeng, Gu, Yilu, Yu, Ying, Li, Min, Chen, Xiaowen, Fan, Mengqi, Jia, Yujie, Tian, Liping, Xiang, Mingdeng, Yu, Yunjiang

Publikováno v: In Journal of Hazardous Materials 5 September 2024 476