Zobrazeno 1 - 10
of 28 714
pro vyhledávání: '"A A, Hamdan"'
Autor:
Rodriguez, Pedro Sales, Robinson, John M., Jepsen, Paul Niklas, He, Zhiyang, Duckering, Casey, Zhao, Chen, Wu, Kai-Hsin, Campo, Joseph, Bagnall, Kevin, Kwon, Minho, Karolyshyn, Thomas, Weinberg, Phillip, Cain, Madelyn, Evered, Simon J., Geim, Alexandra A., Kalinowski, Marcin, Li, Sophie H., Manovitz, Tom, Amato-Grill, Jesse, Basham, James I., Bernstein, Liane, Braverman, Boris, Bylinskii, Alexei, Choukri, Adam, DeAngelo, Robert, Fang, Fang, Fieweger, Connor, Frederick, Paige, Haines, David, Hamdan, Majd, Hammett, Julian, Hsu, Ning, Hu, Ming-Guang, Huber, Florian, Jia, Ningyuan, Kedar, Dhruv, Kornjača, Milan, Liu, Fangli, Long, John, Lopatin, Jonathan, Lopes, Pedro L. S., Luo, Xiu-Zhe, Macrì, Tommaso, Marković, Ognjen, Martínez-Martínez, Luis A., Meng, Xianmei, Ostermann, Stefan, Ostroumov, Evgeny, Paquette, David, Qiang, Zexuan, Shofman, Vadim, Singh, Anshuman, Singh, Manuj, Sinha, Nandan, Thoreen, Henry, Wan, Noel, Wang, Yiping, Waxman-Lenz, Daniel, Wong, Tak, Wurtz, Jonathan, Zhdanov, Andrii, Zheng, Laurent, Greiner, Markus, Keesling, Alexander, Gemelke, Nathan, Vuletić, Vladan, Kitagawa, Takuya, Wang, Sheng-Tao, Bluvstein, Dolev, Lukin, Mikhail D., Lukin, Alexander, Zhou, Hengyun, Cantú, Sergio H.
Realizing universal fault-tolerant quantum computation is a key goal in quantum information science. By encoding quantum information into logical qubits utilizing quantum error correcting codes, physical errors can be detected and corrected, enabling
Externí odkaz:
http://arxiv.org/abs/2412.15165
Autor:
Faruk, Md Omar, Corum, Steven, Hamdan, Zakaraya, Seaver, Alex, Graham, Travis, Blalock, Benjamin J.
Space exploration to have the biosignatures of extraterrestrial life on different planets with oceans in our solar system and beyond requires the design and manufacturing of robust and reliable electronic systems that can be used for sensing, data pr
Externí odkaz:
http://arxiv.org/abs/2411.16093
Heterogeneous graph neural networks have recently gained attention for long document summarization, modeling the extraction as a node classification task. Although effective, these models often require external tools or additional machine learning mo
Externí odkaz:
http://arxiv.org/abs/2410.21315
Autor:
Gonzalez-Cuadra, Daniel, Hamdan, Majd, Zache, Torsten V., Braverman, Boris, Kornjaca, Milan, Lukin, Alexander, Cantu, Sergio H., Liu, Fangli, Wang, Sheng-Tao, Keesling, Alexander, Lukin, Mikhail D., Zoller, Peter, Bylinskii, Alexei
Lattice gauge theories (LGTs) describe a broad range of phenomena in condensed matter and particle physics. A prominent example is confinement, responsible for bounding quarks inside hadrons such as protons or neutrons. When quark-antiquark pairs are
Externí odkaz:
http://arxiv.org/abs/2410.16558
Modern high performance computers are massively parallel; for many PDE applications spatial parallelism saturates long before the computer's capability is reached. Parallel-in-time methods enable further speedup beyond spatial saturation by solving m
Externí odkaz:
http://arxiv.org/abs/2409.18792
Autor:
Bazaluk, Bruna, Hamdan, Mosab, Ghaleb, Mustafa, Gismalla, Mohammed S. M., da Silva, Flavio S. Correa, Batista, Daniel Macêdo
The classification of IoT traffic is important to improve the efficiency and security of IoT-based networks. As the state-of-the-art classification methods are based on Deep Learning, most of the current results require a large amount of data to be t
Externí odkaz:
http://arxiv.org/abs/2407.19051
We present a unified approach to obtain scaling limits of neural networks using the genus expansion technique from random matrix theory. This approach begins with a novel expansion of neural networks which is reminiscent of Butcher series for ODEs, a
Externí odkaz:
http://arxiv.org/abs/2407.08459
Autor:
Kornjača, Milan, Hu, Hong-Ye, Zhao, Chen, Wurtz, Jonathan, Weinberg, Phillip, Hamdan, Majd, Zhdanov, Andrii, Cantu, Sergio H., Zhou, Hengyun, Bravo, Rodrigo Araiza, Bagnall, Kevin, Basham, James I., Campo, Joseph, Choukri, Adam, DeAngelo, Robert, Frederick, Paige, Haines, David, Hammett, Julian, Hsu, Ning, Hu, Ming-Guang, Huber, Florian, Jepsen, Paul Niklas, Jia, Ningyuan, Karolyshyn, Thomas, Kwon, Minho, Long, John, Lopatin, Jonathan, Lukin, Alexander, Macrì, Tommaso, Marković, Ognjen, Martínez-Martínez, Luis A., Meng, Xianmei, Ostroumov, Evgeny, Paquette, David, Robinson, John, Rodriguez, Pedro Sales, Singh, Anshuman, Sinha, Nandan, Thoreen, Henry, Wan, Noel, Waxman-Lenz, Daniel, Wong, Tak, Wu, Kai-Hsin, Lopes, Pedro L. S., Boger, Yuval, Gemelke, Nathan, Kitagawa, Takuya, Keesling, Alexander, Gao, Xun, Bylinskii, Alexei, Yelin, Susanne F., Liu, Fangli, Wang, Sheng-Tao
Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite this promise, most contemporary quantum methods require significant res
Externí odkaz:
http://arxiv.org/abs/2407.02553
Central to the Transformer architectures' effectiveness is the self-attention mechanism, a function that maps queries, keys, and values into a high-dimensional vector space. However, training the attention weights of queries, keys, and values is non-
Externí odkaz:
http://arxiv.org/abs/2405.13901
Autor:
Arguin, Louis-Pierre, Hamdan, Jad
We derive precise upper bounds for the maximum of the Riemann zeta function on short intervals on the critical line, showing for any $\theta\in(-1,0]$, the set of $t\in [T,2T]$ for which $$\max_{|h|\leq \log^\theta T}|\zeta(\tfrac{1}{2}+it+ih)|>\exp\
Externí odkaz:
http://arxiv.org/abs/2405.06474