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20192026
most citedIn-Memory and Error-Immune Differential RRAM Implementation of Binarized Deep Neural Networks

83 citations · 114 across the 13 of their papers we have counts for

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13 papers · 1 filter

cs.ET2026

Forward-only learning in memristor arrays with month-scale stability

Adrien Renaudineau, Mamadou Hawa Diallo, Théo Dupuis +12

Turning memristor arrays from efficient inference engines into systems capable of on-chip learning has proved difficult. Weight updates have a high energy cost and cause device wea…

cs.ET2024

The Logarithmic Memristor-Based Bayesian Machine

Clément Turck, Kamel-Eddine Harabi, Adrien Pontlevy +9

The demand for explainable and energy-efficient artificial intelligence (AI) systems for edge computing has led to significant interest in electronic systems dedicated to Bayesian…

cs.ET2023★ 1 cited

Powering AI at the Edge: A Robust, Memristor-based Binarized Neural Network with Near-Memory Computing and Miniaturized Solar Cell

Fadi Jebali, Atreya Majumdar, Clément Turck +13

Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired…

cs.ET2023★ 3 cited

A Multimode Hybrid Memristor-CMOS Prototyping Platform Supporting Digital and Analog Projects

Kamel-Eddine Harabi, Clement Turck, Marie Drouhin +7

We present an integrated circuit fabricated in a process co-integrating CMOS and hafnium-oxide memristor technology, which provides a prototyping platform for projects involving me…

cs.ET2021

A Memristor-Based Bayesian Machine

Kamel-Eddine Harabi, Tifenn Hirtzlin, Clément Turck +7

In recent years, a considerable research effort has shown the energy benefits of implementing neural networks with memristors or other emerging memory technologies. However, for ex…

cs.ET2020

Embracing the Unreliability of Memory Devices for Neuromorphic Computing

Marc Bocquet, Tifenn Hirtzlin, Jacques-Olivier Klein +4

The emergence of resistive non-volatile memories opens the way to highly energy-efficient computation near- or in-memory. However, this type of computation is not compatible with c…