Advanced search

Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–4 of 4 results
Advanced filters: Author: Maxence Ernoult Clear advanced filters

  • Deep neural networks usually rapidly forget the previously learned tasks while training new ones. Laborieux et al. propose a method for training binarized neural networks inspired by neuronal metaplasticity that allows to avoid catastrophic forgetting and is relevant for neuromorphic applications.

    • Axel Laborieux
    • Maxence Ernoult
    • Damien Querlioz
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-12

  • Spin-torque nano-oscillators have sparked interest for their potential in neuromorphic computing, however concrete demonstration are limited. Here, Romera et al show how spin-torque nano-oscillators can mutually synchronise and recognize temporal patterns, much like neurons, illustrating their potential for neuromorphic computing.

    • Miguel Romera
    • Philippe Talatchian
    • Julie Grollier
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-7

  • A network of four spin-torque nano-oscillators can be trained in real time to recognize spoken vowels, in a simple and scalable approach that could be exploited for large-scale neural networks.

    • Miguel Romera
    • Philippe Talatchian
    • Julie Grollier
    Research
    Nature
    Volume: 563, P: 230-234