Zobrazeno 1 - 10
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pro vyhledávání: '"Tibrewal A"'
The Global Methane Pledge and other methane measures may potentially undermine CO2 mitigation in certain countries, unless they are considered as additional to the existing Nationally Determined Contributions to strengthen overall greenhouse gas emis
Externí odkaz:
http://arxiv.org/abs/2402.04749
To assess the impact of potential future climate pledges after the first Global Stocktake, we propose a simple, transparent framework for developing emission and temperature scenarios by country. We show that current pledges with unconditional target
Externí odkaz:
http://arxiv.org/abs/2312.16326
In this evolving era of machine learning security, membership inference attacks have emerged as a potent threat to the confidentiality of sensitive data. In this attack, adversaries aim to determine whether a particular point was used during the trai
Externí odkaz:
http://arxiv.org/abs/2311.15373
Autor:
Tibrewal, Yashvir, Dwivedi, Nishchal
Studying water droplets is a rich lesson in fields of fluid dynamics, nonlinear systems, and differential equations. Understanding various physical aspects of raindrops can help us in understanding drop dynamics, rainfall density estimation, size dis
Externí odkaz:
http://arxiv.org/abs/2310.18943
Publikováno v:
Phys. Rev. D 109, 043037 - Published 21 February 2024
Most gravitational wave (GW) events observed by the LIGO and Virgo detectors are consistent with mergers of binary black holes (BBHs) on quasi-circular orbits. However, some events are also consistent with non-zero orbital eccentricity, which can ind
Externí odkaz:
http://arxiv.org/abs/2309.16638
Autor:
Kushal Tibrewal, Philippe Ciais, Marielle Saunois, Adrien Martinez, Xin Lin, Joel Thanwerdas, Zhu Deng, Frederic Chevallier, Clément Giron, Clément Albergel, Katsumasa Tanaka, Prabir Patra, Aki Tsuruta, Bo Zheng, Dmitry Belikov, Yosuke Niwa, Rajesh Janardanan, Shamil Maksyutov, Arjo Segers, Zitely A. Tzompa-Sosa, Philppe Bousquet, Jean Sciare
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-12 (2024)
Abstract Emissions from fossil fuel exploitation are a leading contributor to global anthropogenic methane emissions, but are highly uncertain. The lack of reliable estimates hinders monitoring of the progress on pledges towards methane reductions. H
Externí odkaz:
https://doaj.org/article/f01dadcd7e294b5f872d3e42d987cbc4
Publikováno v:
In Journal of Optometry July-September 2024 17(3)
Autor:
Rupesh Raina, MD, Kush Doshi, Sidharth Sethi, MD, Bryce Pember, Rohan Kumar, Khalid A. Alhasan, MD, Mitchell C. Boshkos, MD, Abhishek Tibrewal, MD, Jirair K. Bedoyan, MD, PhD
Publikováno v:
Kidney Medicine, Vol 6, Iss 1, Pp 100751- (2024)
Externí odkaz:
https://doaj.org/article/f5123294157f471393677b8fff720ec6
Autor:
Shen, Jonathan, Nguyen, Patrick, Wu, Yonghui, Chen, Zhifeng, Chen, Mia X., Jia, Ye, Kannan, Anjuli, Sainath, Tara, Cao, Yuan, Chiu, Chung-Cheng, He, Yanzhang, Chorowski, Jan, Hinsu, Smit, Laurenzo, Stella, Qin, James, Firat, Orhan, Macherey, Wolfgang, Gupta, Suyog, Bapna, Ankur, Zhang, Shuyuan, Pang, Ruoming, Weiss, Ron J., Prabhavalkar, Rohit, Liang, Qiao, Jacob, Benoit, Liang, Bowen, Lee, HyoukJoong, Chelba, Ciprian, Jean, Sébastien, Li, Bo, Johnson, Melvin, Anil, Rohan, Tibrewal, Rajat, Liu, Xiaobing, Eriguchi, Akiko, Jaitly, Navdeep, Ari, Naveen, Cherry, Colin, Haghani, Parisa, Good, Otavio, Cheng, Youlong, Alvarez, Raziel, Caswell, Isaac, Hsu, Wei-Ning, Yang, Zongheng, Wang, Kuan-Chieh, Gonina, Ekaterina, Tomanek, Katrin, Vanik, Ben, Wu, Zelin, Jones, Llion, Schuster, Mike, Huang, Yanping, Chen, Dehao, Irie, Kazuki, Foster, George, Richardson, John, Macherey, Klaus, Bruguier, Antoine, Zen, Heiga, Raffel, Colin, Kumar, Shankar, Rao, Kanishka, Rybach, David, Murray, Matthew, Peddinti, Vijayaditya, Krikun, Maxim, Bacchiani, Michiel A. U., Jablin, Thomas B., Suderman, Rob, Williams, Ian, Lee, Benjamin, Bhatia, Deepti, Carlson, Justin, Yavuz, Semih, Zhang, Yu, McGraw, Ian, Galkin, Max, Ge, Qi, Pundak, Golan, Whipkey, Chad, Wang, Todd, Alon, Uri, Lepikhin, Dmitry, Tian, Ye, Sabour, Sara, Chan, William, Toshniwal, Shubham, Liao, Baohua, Nirschl, Michael, Rondon, Pat
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models are composed of modular building blocks that are flexible and easily ex
Externí odkaz:
http://arxiv.org/abs/1902.08295
We consider an ad hoc network where multiple users access the same set of channels. The channel characteristics are unknown and could be different for each user (heterogeneous). No controller is available to coordinate channel selections by the users
Externí odkaz:
http://arxiv.org/abs/1901.03868