175 citations · 180 across the 4 of their papers we have counts for
6 papers
Spatio-temporal Learning with Arrays of Analog Nanosynapses
Christopher H. Bennett, Damien Querlioz, Jacques-Olivier Klein
Emerging nanodevices such as resistive memories are being considered for hardware realizations of a variety of artificial neural networks (ANNs), including highly promising online…
A Neural Network Based on Synchronized Pairs of Nano-Oscillators
Damir Vodenicarevic, Nicolas Locatelli, Damien Querlioz
Artificial neural networks are intensively used to perform cognitive tasks such as image classification on traditional computers. With the end of CMOS scaling and increasing demand…
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…
Synchronization Detection in Networks of Coupled Oscillators for Pattern Recognition
Damir Vodenicarevic, Nicolas Locatelli, Julie Grollier +1
Coupled oscillator-based networks are an attractive approach for implementing hardware neural networks based on emerging nanotechnologies. However, the readout of the state of a co…
Exploiting the Short-term to Long-term Plasticity Transition in Memristive Nanodevice Learning Architectures
Christopher H. Bennett, Selina La Barbera, Adrien F. Vincent +2
Memristive nanodevices offer new frontiers for computing systems that unite arithmetic and memory operations on-chip. Here, we explore the integration of electrochemical metallizat…
Controlling the phase locking of unstable magnetic bits for ultra-low power computation
A. Mizrahi, N. Locatelli, R. Lebrun +6
When fabricating magnetic memories, one of the main challenges is to maintain the bit stability while downscaling. Indeed, for magnetic volumes of a few thousand nm3, the energy ba…