no code implementations • 18 Jul 2023 • Frédéric Marcotte, Pierre-Antoine Mouny, Victor Yon, Gebremedhin A. Dagnew, Bohdan Kulchytskyy, Sophie Rochette, Yann Beilliard, Dominique Drouin, Pooya Ronagh
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors.
no code implementations • 29 May 2023 • Philippe Drolet, Raphaël Dawant, Victor Yon, Pierre-Antoine Mouny, Matthieu Valdenaire, Javier Arias Zapata, Pierre Gliech, Sean U. N. Wood, Serge Ecoffey, Fabien Alibart, Yann Beilliard, Dominique Drouin
Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1R) counterparts in terms of the integration density.
no code implementations • 25 May 2023 • Joao Henrique Quintino Palhares, Yann Beilliard, Jury Sandrini, Franck Arnaud, Kevin Garello, Guillaume Prenat, Lorena Anghel, Fabien Alibart, Dominique Drouin, Philippe Galy
In this work we report a study and a co-design methodology of an analog SNN crossbar output circuit designed in a 28nm FD-SOI technology node that comprises a tunable current attenuator and a leak-integrate and fire neurons that would enable the integration of emerging non-volatile memories (eNVMs) for synaptic arrays based on various technologies including phase change (PCRAM), oxide-based (OxRAM), spin transfer and spin orbit torque magnetic memories (STT, SOT-MRAM).
no code implementations • 21 Mar 2022 • Nikhil Garg, Ismael Balafrej, Terrence C. Stewart, Jean Michel Portal, Marc Bocquet, Damien Querlioz, Dominique Drouin, Jean Rouat, Yann Beilliard, Fabien Alibart
To validate the system-level performance of VDSP, we train a single-layer spiking neural network (SNN) for the recognition of handwritten digits.
1 code implementation • 9 Jun 2021 • Nikhil Garg, Ismael Balafrej, Yann Beilliard, Dominique Drouin, Fabien Alibart, Jean Rouat
Using a simple machine learning algorithm after spike encoding, we report performance higher than the state-of-the-art spiking neural networks on two open-source datasets for hand gesture recognition.