582 citations · 1.5k across the 53 of their papers we have counts for
60 papers
Synaptic metaplasticity with multi-level memristive devices
Simone D'Agostino, Filippo Moro, Tifenn Hirtzlin +5
Deep learning has made remarkable progress in various tasks, surpassing human performance in some cases. However, one drawback of neural networks is catastrophic forgetting, where…
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…
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…
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…
Characterization and modeling of spiking and bursting in experimental NbOx neuron
Marie Drouhin, Shuai Li, Matthieu Grelier +7
Hardware spiking neural networks hold the promise of realizing artificial intelligence with high energy efficiency. In this context, solid-state and scalable memristors can be used…
Experimental demonstration of Single-Level and Multi-Level-Cell RRAM-based In-Memory Computing with up to 16 parallel operations
E. Esmanhotto, T. Hirtzlin, N. Castellani +7
Crossbar arrays of resistive memories (RRAM) hold the promise of enabling In-Memory Computing (IMC), but essential challenges due to the impact of device imperfection and device en…