5 citations · 17 across the 11 of their papers we have counts for
11 papers
Functional Interface Blocks for Neuromorphic Hardware: A Junction-Centered Framework
Wellington Avelino, Yann Beillard, Fabien Allibart +2
Heterogeneous neuromorphic hardware integrates devices with dissimilar electrical characteristics and dynamics, making functional compatibility at their interconnections a primary…
Unsupervised local learning based on voltage-dependent synaptic plasticity for resistive and ferroelectric synapses
Nikhil Garg, Ismael Balafrej, Joao Henrique Quintino Palhares +11
The deployment of AI on edge computing devices faces significant challenges related to energy consumption and functionality. These devices could greatly benefit from brain-inspired…
Towards a Cryogenic CMOS-Memristor Neural Decoder for Quantum Error Correction
Pierre-Antoine Mouny, Maher Benhouria, Victor Yon +6
This paper presents a novel approach utilizing a scalable neural decoder application-specific integrated circuit (ASIC) based on metal oxide memristors in a 180nm CMOS technology.…
Experimental online quantum dots charge autotuning using neural networks
Victor Yon, Bastien Galaup, Claude Rohrbacher +11
Spin-based semiconductor qubits hold promise for scalable quantum computing, yet they require reliable autonomous calibration procedures. This study presents an experimental demons…
Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits
Nikhil Garg, Davide Florini, Patrick Dufour +8
Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron wi…
Robust quantum dots charge autotuning using neural network uncertainty
Victor Yon, Bastien Galaup, Claude Rohrbacher +10
This study presents a machine-learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention, addressing one of the significant…
Towards scalable cryogenic quantum dot biasing using memristor-based DC sources
Pierre-Antoine Mouny, Raphaël Dawant, Patrick Dufour +5
Cryogenic memristor-based DC sources offer a promising avenue for in situ biasing of quantum dot arrays. In this study, we present experimental results and discuss the scaling pote…
Analog programming of CMOS-compatible AlO/TiO memristor at 4.2 K after metal-insulator transition suppression by cryogenic reforming
Pierre-Antoine Mouny, Raphaël Dawant, Bastien Galaup +4
The exploration of memristors' behavior at cryogenic temperatures has become crucial due to the growing interest in quantum computing and cryogenic electronics. In this context, ou…
A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction
Victor Yon, Frédéric Marcotte, Pierre-Antoine Mouny +6
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 pr…
Hardware-aware Training Techniques for Improving Robustness of Ex-Situ Neural Network Transfer onto Passive TiO2 ReRAM Crossbars
Philippe Drolet, Raphaël Dawant, Victor Yon +9
Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1…
A tunable and versatile 28nm FD-SOI crossbar output circuit for low power analog SNN inference with eNVM synapses
Joao Henrique Quintino Palhares, Yann Beilliard, Jury Sandrini +7
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 atten…