Zobrazeno 1 - 7
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pro vyhledávání: '"Laurie E Calvet"'
Autor:
Laurie E Calvet
Publikováno v:
PLoS ONE, Vol 17, Iss 12, p e0279455 (2022)
Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for
Externí odkaz:
https://doaj.org/article/e1553c71efb04e8b84f50e8007262a1b
Publikováno v:
PLoS ONE, Vol 15, Iss 10, p e0239700 (2020)
In the past two decades, research into the biochemical, biophysical and structural properties of the ribosome have revealed many different steps of protein translation. Nevertheless, a complete understanding of how they lead to a rapid and accurate p
Externí odkaz:
https://doaj.org/article/d75adb47a3c64e609eef3d2c136f7209
Autor:
Laurie E. Calvet, Sami El‐Nakouzi, Zonglong Li, Yerin Kim, Amer Zaibi, Patryk Golec, Ie Mei Bhattacharyya, Yvan Bonnassieux, Lina Kadura, Benjamin Iñiguez
Publikováno v:
Advanced Electronic Materials, Vol 10, Iss 12, Pp n/a-n/a (2024)
Abstract There is increasing interest in using specialized circuits based on emerging technologies to develop a new generation of smart devices. The process and device variability exhibited by such materials, however, can present substantial challeng
Externí odkaz:
https://doaj.org/article/d241e365557f4c71a5d786d78854b2e7
Publikováno v:
Frontiers in Computational Neuroscience, Vol 17 (2023)
Classification and recognition tasks performed on photonic hardware-based neural networks often require at least one offline computational step, such as in the increasingly popular reservoir computing paradigm. Removing this offline step can signific
Externí odkaz:
https://doaj.org/article/8603911d08934ac196bb1f0fef2646c8
Publikováno v:
Nature Nanotechnology. 17:336-336
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e0d686cd7486f592e5230ccee7b8f64
https://doi.org/10.1038/s41565-022-01093-5
https://doi.org/10.1038/s41565-022-01093-5
Autor:
Christopher H. Bennett, Vivek Parmar, Laurie E. Calvet, Jacques-Olivier Klein, Manan Suri, Matthew J. Marinella, Damien Querlioz
Publikováno v:
IEEE Access, Vol 7, Pp 73938-73953 (2019)
Recently, a Cambrian explosion of a novel, non-volatile memory (NVM) devices known as memristive devices have inspired effort in building hardware neural networks that learn like the brain. Early experimental prototypes built simple perceptrons from
Externí odkaz:
https://doaj.org/article/47533fa00ed34d889501fb275d953415