175 citations · 184 across the 7 of their papers we have counts for
7 papers
Multilayer spintronic neural networks with radio-frequency connections
Andrew Ross, Nathan Leroux, Arnaud de Riz +18
Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. Thes…
Memristor Hardware-Friendly Reinforcement Learning
Nan Wu, Adrien Vincent, Dmitri Strukov +1
Recently, significant progress has been made in solving sophisticated problems among various domains by using reinforcement learning (RL), which allows machines or agents to learn…
Implementing Binarized Neural Networks with Magnetoresistive RAM without Error Correction
Tifenn Hirtzlin, Bogdan Penkovsky, Jacques-Olivier Klein +5
One of the most exciting applications of Spin Torque Magnetoresistive Random Access Memory (ST-MRAM) is the in-memory implementation of deep neural networks, which could allow impr…
Use of Magnetoresistive Random-Access Memory as Approximate Memory for Training Neural Networks
Nicolas Locatelli, Adrien F. Vincent, Damien Querlioz
Hardware neural networks that implement synaptic weights with embedded non-volatile memory, such as spin torque memory (ST-MRAM), are a major lead for low energy artificial intelli…
Compact Modeling of I-V Characteristics, Temperature Dependency, Variations, and Noise of Integrated, Reproducible Metal-Oxide Memristors
H. Nili, A. Vincent, M. Prezioso +3
We present a comprehensive phenomenological model for the crossbar integrated metal-oxide continuous-state memristors. The model consists of static and dynamic equations, which are…
Low-Energy Truly Random Number Generation with Superparamagnetic Tunnel Junctions for Unconventional Computing
Damir Vodenicarevic, Nicolas Locatelli, Alice Mizrahi +10
Low-energy random number generation is critical for many emerging computing schemes proposed to complement or replace von Neumann architectures. However, current random number gene…