Paper Title: Advanced Design Methods From Materials and Devices to Circuits for Brain-Inspired Oscillatory Neural Networks for Edge Computing In this paper, we assess an innovative concept of emulating biological neurons with oscillators to implement an oscillatory neural [...]
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 [...]
Today, Dr. Stefania Carapezzi, EU H2020 NeurONN, CNRS Occitanie Est, LIRMM gives a Talk on simulations of VO2 oscillators for ONN applications in the frame of virtual 2021 Albany Nanotechnology Symposium at 19h00 pm CET! Stay tuned! https://albanynanotechnology.org/contributed-talks/
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 [...]
On July 13th 2021, G. Boschetto, Post-Doctoral Researcher, CNRS, LIRMM presented his work on the atomistic modelling of 2D materials for both biosensing and 2D memristor devices at the 15th International Conference on Materials Chemistry (RSC MC15), which took place [...]
On October 13th, our PhD student Madeleine Abernot, CNRS, LIRMM presented her poster on “Mobile Robot Obstacle Avoidance with Oscillatory Neural Networks on FPGA” in the IBM/IEEE AI Compute Symposium. The poster won the third place of track 2 – [...]
Dr. Stefania Carapezzi presented her paper at the 2021 Fall Meeting of the European Materials Research Society (E-MRS). Her work is entitled “VO2 Oscillators on Si Platform for Neuromorphic Computing Applications”.
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 [...]
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 [...]
Dr. Aida Todri-Sanial gave a Keynote talk at the Ecole National School of Chemistry of Montpellier. Her talk was on “Energy Consumption and Electronics Devices: Why we need to re-think chip design for AI?”.