Recent paper by Dr. G. Boschetto featuring on the front cover of ACS Applied Nano Materials

We are thrilled to announce that the recent paper by Dr. Gabriele Boschetto, EU H2020 NeurONN, CNRS, titled "Ab Initio Computer Simulations on Interfacial Properties of Single-Layer MoS2 and Au Contacts for Two-Dimensional Nanodevices" is now featuring on the front [...]

Dr. Stefania Carapezzi publishes at Springer Nature in MRS Communications

We are proud for the publication of Dr. Stefania Carapezzi, CNRS at Springer Nature in MRS Communications. Her paper is on Electro-thermal simulations of beyond-CMOS vanadium dioxide devices and oscillators. The quest for energy-efficient devices is a main challenge in this highly-technological world. [...]

PhD Student Corentin Delacour publishes at Frontiers in Neuroscience

Paper Title: Mapping Hebbian Learning Rules to Coupling Resistances for Oscillatory Neural Networks Oscillatory Neural Network (ONN) is an emerging neuromorphic architecture with oscillators representing neurons and information encoded in oscillator's phase relations. In an ONN, oscillators are [...]

ACM Europe Summer School – Best Poster Award

Madeleine Abernot, PhD student at EU H2020 NEURONN, Centre national de la recherche scientifique, LIRMM, received one of the Best Poster Awards for her presentation on "FPGA Implementation of Oscillatory Neural Networks for Artificial Intelligence Edge Computing" during the ACM [...]

CNRS-CSIC/IMSE-A.I.M Publication at Frontiers in Neuroscience

Paper Title: Digital Implementation of Oscillatory Neural Network for Image Recognition Applications Computing paradigm based on von Neuman architectures cannot keep up with the ever-increasing data growth (also called “data deluge gap”). This has resulted in investigating novel [...]

How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase

Check out our recent article on brain-inspired computing with oscillatory neural networks for solving complex associative problems. This original work exploits the sub-harmonic injection locking method for controlling the oscillatory states of coupled oscillators to facilitate learning and inference. These [...]

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