D
Damien Querlioz
Researcher at Université Paris-Saclay
Publications - 210
Citations - 8932
Damien Querlioz is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Artificial neural network & Neuromorphic engineering. The author has an hindex of 41, co-authored 192 publications receiving 6642 citations. Previous affiliations of Damien Querlioz include University of Paris-Sud & Centre national de la recherche scientifique.
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Journal ArticleDOI
Neuromorphic computing with nanoscale spintronic oscillators
Jacob Torrejon,Mathieu Riou,Flavio Abreu Araujo,Sumito Tsunegi,Guru Khalsa,Damien Querlioz,P. Bortolotti,Vincent Cros,Kay Yakushiji,Akio Fukushima,Hitoshi Kubota,Shinji Yuasa,Mark D. Stiles,Julie Grollier +13 more
TL;DR: In this article, a magnetic tunnel junction (MTJ) was used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks.
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Spintronic Nanodevices for Bioinspired Computing
TL;DR: This paper shows how spintronics can be used for bioinspired computing, and reviews the different approaches that have been proposed, the recent advances in this direction, and the challenges toward fully integrated spintronic complementary metal-oxide-semiconductor (CMOS) bioinspired hardware.
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Vowel recognition with four coupled spin-torque nano-oscillators
M. Romera,Philippe Talatchian,Sumito Tsunegi,Flavio Abreu Araujo,Flavio Abreu Araujo,Vincent Cros,Paolo Bortolotti,Juan Trastoy,Kay Yakushiji,Akio Fukushima,Hitoshi Kubota,Shinji Yuasa,Maxence Ernoult,Damir Vodenicarevic,Tifenn Hirtzlin,Nicolas Locatelli,Damien Querlioz,Julie Grollier +17 more
TL;DR: In this paper, the authors demonstrate that non-trivial pattern classification tasks can be achieved with small hardware neural networks by endowing them with nonlinear dynamical features such as oscillations and synchronization.
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Immunity to Device Variations in a Spiking Neural Network With Memristive Nanodevices
TL;DR: A novel neural network-based computing paradigm, which exploits their specific physics, and which has virtual immunity to their variability, is proposed, which is particularly robust to read disturb effects and does not require unrealistic control on the devices’ conductance.
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Spin-Transfer Torque Magnetic Memory as a Stochastic Memristive Synapse for Neuromorphic Systems
Adrien F. Vincent,Jerome Larroque,Nicolas Locatelli,Nesrine Ben Romdhane,Olivier Bichler,Christian Gamrat,Weisheng Zhao,Jacques-Olivier Klein,S. Galdin-Retailleau,Damien Querlioz +9 more
TL;DR: It is shown that when used in a non-conventional regime, STT-MTJs can additionally act as a stochastic memristive device, appropriate to implement a “synaptic” function in robust, low power, cognitive-type systems.