Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Floris Laporte"'
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract Nonlinear activation is a crucial building block of most machine-learning systems. However, unlike in the digital electrical domain, applying a saturating nonlinear function in a neural network in the analog optical domain is not as easy, es
Externí odkaz:
https://doaj.org/article/d92a385b625b4cbab5f599ed38e7565d
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract Using optical hardware for neuromorphic computing has become more and more popular recently, due to its efficient high-speed data processing capabilities and low power consumption. However, there are still some remaining obstacles to realizi
Externí odkaz:
https://doaj.org/article/4f5d98d609b64eea817642000c98823e
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract Photorefractive materials exhibit an interesting plasticity under the influence of an optical field. By extending the finite-difference time-domain method to include the photorefractive effect, we explore how this property can be exploited i
Externí odkaz:
https://doaj.org/article/29b2a9f56c7c4082a9533fd4bbd1c787
Publikováno v:
SCIENTIFIC REPORTS
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports
Using optical hardware for neuromorphic computing has become more and more popular recently due to its efficient high-speed data processing capabilities and low power consumption. However, there are still some remaining obstacles to realizing the vis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ca5bd724d6efdebc0c6a4d8531e7714
https://hdl.handle.net/1854/LU-8716289
https://hdl.handle.net/1854/LU-8716289
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
SCIENTIFIC REPORTS
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
SCIENTIFIC REPORTS
Photorefractive materials exhibit an interesting plasticity under the influence of an optical field. By extending the finite-difference time-domain method to include the photorefractive effect, we explore how this property can be exploited in the con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa523337ac3d35ca2f3a21aa9f441ad2
Autor:
Matthias Freiberger, Andrew Katumba, Chonghuai Ma, Stijn Sackesyn, Floris Laporte, Peter Bienstman, Joni Dambre
Publikováno v:
Natural Computing Series ISBN: 9789811316869
The idea of using photonic systems as reservoirs to perform general-purpose computing was first introduced in 2008. Since then, a wide range of systems using either discrete or integrated optical components has been explored. In this chapter, we summ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::272bdbc56680148b411fe726a8d17ac3
https://doi.org/10.1007/978-981-13-1687-6_17
https://doi.org/10.1007/978-981-13-1687-6_17
Autor:
Joni Dambre, Peter Bienstman, Chonghuai Ma, Floris Laporte, Stijn Sackesyn, Andrew Katumba, Matthias Freiberger, Alessio Lugnan
Publikováno v:
IEEE Journal of Selected Topics in Quantum Electronics
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
We present our latest progress using new neuromorphic paradigms for optical information processing in silicon photonics. We show how passive reservoir computing chips can be used to perform a variety of tasks (bit level tasks, nonlinear dispersion co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d9058374554ae217a1caaa8d41821a8
https://doi.org/10.1109/jstqe.2018.2821843
https://doi.org/10.1109/jstqe.2018.2821843
Autor:
Matthias Freiberger, Andrew Katumba, Alessio Lugnan, Floris Laporte, Chonghuai Ma, Stijn Sackesyn, Joni Dambre, Emmanuel Gooskens, Peter Bienstman
Publikováno v:
APL Photonics
APL PHOTONICS
APL PHOTONICS
Photonic neuromorphic computing is attracting tremendous research interest now, catalyzed in no small part by the rise of deep learning in many applications. In this paper, we will review some of the exciting work that has been going in this area and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42d348f1ac39f68c041c67911ea13754
Autor:
Matthias Freiberger, Alessio Lugnan, Andrew Katumba, Stijn Sackesyn, Chonghuai Ma, Joni Dambre, Peter Bienstman, Floris Laporte
Publikováno v:
Photonic Reservoir Computing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::852d7bd8d9f037936e95d1b0531cbabf
https://doi.org/10.1515/9783110583496-003
https://doi.org/10.1515/9783110583496-003
Publikováno v:
SCIENTIFIC REPORTS
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports
We propose a new method for performing photonic circuit simulations based on the scatter matrix formalism. We leverage the popular deep-learning framework PyTorch to reimagine photonic circuits as sparsely connected complex-valued neural networks. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::230dd3371414c68f884f0f81279b7611
https://doi.org/10.1038/s41598-019-42408-2
https://doi.org/10.1038/s41598-019-42408-2