Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Axel Laborieux"'
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Deep neural networks usually rapidly forget the previously learned tasks while training new ones. Laborieux et al. propose a method for training binarized neural networks inspired by neuronal metaplasticity that allows to avoid catastrophic forgettin
Externí odkaz:
https://doaj.org/article/e2b90fdc25c546258715984597f47c48
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing Its Gradient Estimator Bias
Autor:
Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Equilibrium Propagation is a biologically-inspired algorithm that trains convergent recurrent neural networks with a local learning rule. This approach constitutes a major lead to allow learning-capable neuromophic systems and comes with strong theor
Externí odkaz:
https://doaj.org/article/a3d825b89aad48b8b6b25d564ec23b01
Autor:
Etienne Nowak, Damien Querlioz, Marc Bocquet, Axel Laborieux, Atreya Majumdar, Elisa Vianello, Jean-Michel Portal, Tifenn Hirtzlin, Jacques-Olivier Klein
Publikováno v:
IEEE Transactions on Electron Devices
IEEE Transactions on Electron Devices, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
The implementation of current deep learning training algorithms is power-hungry, due to data transfer between memory and logic units. Oxide-based resistive random access memories (RRAMs) are outstanding candidates to implement in-memory computing, wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edcbfdd9a7b73660ad52cf15830ef24e
https://hal.science/hal-03372056/document
https://hal.science/hal-03372056/document
Autor:
Axel Laborieux, J.P. Walder, A. Majumdar, E. Vianello, Tifenn Hirtzlin, Jean-Michel Portal, Damien Querlioz, Marc Bocquet, F. Jebali
Publikováno v:
MWSCAS
2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)
2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Aug 2021, Lansing, France. pp.158-161, ⟨10.1109/MWSCAS47672.2021.9531919⟩
2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)
2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Aug 2021, Lansing, France. pp.158-161, ⟨10.1109/MWSCAS47672.2021.9531919⟩
International audience; Currently, a major trend in artificial intelligence is to implement neural networks at the edge, within circuits with limited memory capacity. To reach this goal, the in-memory or near-memory implementation of low precision ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd17fd1b7d79c26734ef49b1fcd46f13
https://doi.org/10.1109/mwscas47672.2021.9531919
https://doi.org/10.1109/mwscas47672.2021.9531919
Autor:
Marc Bocquet, Damien Querlioz, Jacques-Olivier Klein, Elisa Vianello, Etienne Nowak, Jean-Michel Portal, Axel Laborieux, Tifenn Hirtzlin
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers
IEEE Transactions on Circuits and Systems I: Regular Papers, IEEE, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, IEEE, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a significant lead for reducing the energy consumption of artificial intelligence. To achieve maximum energy effi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aca5a159c791b6a8326502c6aa7983ce
https://hal.archives-ouvertes.fr/hal-02983778/document
https://hal.archives-ouvertes.fr/hal-02983778/document
Autor:
Eduardo Martínez, Damien Querlioz, Mohamed Belmeguenai, Yuting Liu, Jan Vogel, Alexander J. Grutter, Luis Sanchez-Terejina San José, Andrew D. Kent, Axel Laborieux, Shimpei Ono, Mohammed S. El Hadri, Dafiné Ravelosona, Eric E. Fullerton, Elke Arenholtz, Brian B. Maranville, Liza Herrera-Diez, Juergen Langer, Yves Roussigné, Stefania Pizzini, Alessio Lamperti, Jamileh Beik Mohammadi, Andrey Stashkevich, Robert Tolley, Dustin A. Gilbert, S. M. Chérif, Berthold Ocker, Patrick Quarterman
Publikováno v:
Spintronics XIII.
Tuning the Dzyaloshinskii-Moriya interaction (DMI) using electric (E)-fields in magnetic devices has opened up new perspectives for controlling the stabilization of chiral spin structures. Recent efforts have used voltage-induced charge redistributio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a38d8be48dfbda77425c6331f344e35
https://doi.org/10.1117/12.2567644
https://doi.org/10.1117/12.2567644
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Nature Communications
Nature Communications, Nature Publishing Group, 2021, 12 (1), ⟨10.1038/s41467-021-22768-y⟩
Nature Communications
Nature Communications, Nature Publishing Group, 2021, 12 (1), ⟨10.1038/s41467-021-22768-y⟩
While deep neural networks have surpassed human performance in multiple situations, they are prone to catastrophic forgetting: upon training a new task, they rapidly forget previously learned ones. Neuroscience studies, based on idealized tasks, sugg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5d832ad7c2495908bad63ea73712fcd
Autor:
Andrew D. Kent, Stefania Pizzini, M. Salah El Hadri, Yves Roussigné, Axel Laborieux, Alessio Lamperti, Andrey Stashkevich, Y. Liu, Shimpei Ono, Brian B. Maranville, Jürgen Langer, Damien Querlioz, J. B. Mohammedi, Dafiné Ravelosona, E. Arenholtz, Eric E. Fullerton, Eduardo Martínez, Berthold Ocker, Luis Sánchez-Tejerina, L. Herrera Diez, Jan Vogel, Robert Tolley, Dustin A. Gilbert, Alexander J. Grutter, M. Belmeguenai, Patrick Quarterman, S. M. Chérif
Publikováno v:
Physical Review Applied
Physical Review Applied, American Physical Society, 2019, 12 (3), pp.034005. ⟨10.1103/PhysRevApplied.12.034005⟩
Physical Review Applied, 2019, 12 (3), pp.034005. ⟨10.1103/PhysRevApplied.12.034005⟩
Physical Review Applied 12 (2019). doi:10.1103/PhysRevApplied.12.034005
info:cnr-pdr/source/autori:Diez, L. Herrera; Liu, Y. T.; Gilbert, D. A.; Belmeguenai, M.; Vogel, J.; Pizzini, S.; Martinez, E.; Lamperti, A.; Mohammedi, J. B.; Laborieux, A.; Roussigne, Y.; Grutter, A. J.; Arenholtz, E.; Quarterman, P.; Maranville, B.; Ono, S.; El Hadri, M. Salah; Tolley, R.; Fullerton, E. E.; Sanchez-Tejerina, L.; Stashkevich, A.; Cherif, S. M.; Kent, A. D.; Querlioz, D.; Langer, J.; Ocker, B.; Ravelosona, D./titolo:Nonvolatile Ionic Modification of the Dzyaloshinskii-Moriya Interaction/doi:10.1103%2FPhysRevApplied.12.034005/rivista:Physical Review Applied/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume:12
Physical Review Applied, American Physical Society, 2019, 12 (3), pp.034005. ⟨10.1103/PhysRevApplied.12.034005⟩
Physical Review Applied, 2019, 12 (3), pp.034005. ⟨10.1103/PhysRevApplied.12.034005⟩
Physical Review Applied 12 (2019). doi:10.1103/PhysRevApplied.12.034005
info:cnr-pdr/source/autori:Diez, L. Herrera; Liu, Y. T.; Gilbert, D. A.; Belmeguenai, M.; Vogel, J.; Pizzini, S.; Martinez, E.; Lamperti, A.; Mohammedi, J. B.; Laborieux, A.; Roussigne, Y.; Grutter, A. J.; Arenholtz, E.; Quarterman, P.; Maranville, B.; Ono, S.; El Hadri, M. Salah; Tolley, R.; Fullerton, E. E.; Sanchez-Tejerina, L.; Stashkevich, A.; Cherif, S. M.; Kent, A. D.; Querlioz, D.; Langer, J.; Ocker, B.; Ravelosona, D./titolo:Nonvolatile Ionic Modification of the Dzyaloshinskii-Moriya Interaction/doi:10.1103%2FPhysRevApplied.12.034005/rivista:Physical Review Applied/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume:12
International audience; The possibility to tune the Dzyaloshinskii Moriya interaction (DMI) by electric (E) field gating in ultra-thin magnetic materials has opened new perspectives in terms of controlling the stabilization of chiral spin structures.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e8201d2d696678403d2da6324d0cd29
https://hal.archives-ouvertes.fr/hal-02331252
https://hal.archives-ouvertes.fr/hal-02331252
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing Its Gradient Estimator Bias
Autor:
'Axel Laborieux
Publikováno v:
Maxence Ernoult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::381a309bcf45bf4f0fc492fef35290b0