Zobrazeno 1 - 10
of 985
pro vyhledávání: '"Moore, Nick"'
Autor:
Nair, Lakshmi, Widemann, David, Turcott, Brad, Moore, Nick, Wleklinski, Alexandra, Bunandar, Darius, Papavasileiou, Ioannis, Wang, Shihu, Logan, Eric
Photonic computing promises faster and more energy-efficient deep neural network (DNN) inference than traditional digital hardware. Advances in photonic computing can have profound impacts on applications such as autonomous driving and defect detecti
Externí odkaz:
http://arxiv.org/abs/2309.16783
In this work, we develop a computational method that to provide realtime detection for water bottom topography based on observations on surface measurements, and we design an inverse problem to achieve this task. The forward model that we use to desc
Externí odkaz:
http://arxiv.org/abs/2301.07797
Autor:
Demirkiran, Cansu, Eris, Furkan, Wang, Gongyu, Elmhurst, Jonathan, Moore, Nick, Harris, Nicholas C., Basumallik, Ayon, Reddi, Vijay Janapa, Joshi, Ajay, Bunandar, Darius
Publikováno v:
J. Emerg. Technol. Comput. Syst. 19, 4, Article 30 (October 2023)
The number of parameters in deep neural networks (DNNs) is scaling at about 5$\times$ the rate of Moore's Law. To sustain this growth, photonic computing is a promising avenue, as it enables higher throughput in dominant general matrix-matrix multipl
Externí odkaz:
http://arxiv.org/abs/2109.01126
Autor:
Simaika, John P., Stribling, James, Lento, Jennifer, Bruder, Andreas, Poikane, Sandra, Moretti, Marcelo S., Rivers-Moore, Nick, Meissner, Kristian, Macadam, Craig R.
Publikováno v:
In Science of the Total Environment 25 March 2024 918
Publikováno v:
Water SA. Jul2023, Vol. 49 Issue 3, p251-259. 9p.
Akademický článek
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Autor:
Baxter-Moore, Nick1 (AUTHOR) nbaxtermoore@brocku.ca, Eagles, Munroe2 (AUTHOR), McLean, Dylan S.3 (AUTHOR), Villeneuve-Siconnelly, Katryne4 (AUTHOR)
Publikováno v:
American Review of Canadian Studies. Jun2023, Vol. 53 Issue 2, p239-254. 16p.
Autor:
Anghel, Sergiu, Singh, Akshay, Passmann, Felix, Iwata, Hikaru, Moore, Nick, Yusa, Go, Li, Xiaoqin, Betz, Markus
Exciton, trion and electron spin dynamics in a 20 nm wide modulation-doped GaAs single quantum well are investigated using resonant ultrafast two-color Kerr rotation spectroscopy. Excitons and trions are selectively detected by resonant probe pulses
Externí odkaz:
http://arxiv.org/abs/1605.01771
Akademický článek
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