Publications

Our recent work  “Supported Pt Nanoclusters on Single-Layer MoS2 for the Detection of Cortisol: From Atomistic Scale to Device” (10.1021/acsaelm.2c01722) is now published in ACS Applied Electronic Materials. Our image has been chosen as the Front Cover Art of [...]

Our recent article on ‘Oscillatory Neural Network Learning for Pattern Recognition: An On-Chip Learning Perspective and Implementation’ has been accepted a the Frontiers in Neuroscience journal. Congratulations to our PhD student Madeleine Abernot on this great achievement! Article link: [...]

PhD student Madeleine Abernot presented at GDR SOC Colloquium  2023 her latest work on ‘Digital Oscillatory Neural Networks for Edge AI Applications” in the framework of H2020 NeurONN project. Detailed programme: https://www.gdr-soc.cnrs.fr/programme-detaille-2023/

PhD student Madeleine Abernot presented at IEEE ISCAS 2023 her latest work on ‘Two-Layered Oscillatory Neural Networks with Analog Feedforward Majority Gate for Image Detection Application” in the framework of the H2020 NeurONN project. This work is a collaborative [...]

Our PhD student Madeleine Abernot presented her latest work at the Neuro-Inspired Computing Elements (NICE) Workshop. Her talk was on feature detection algorithms using oscillatory neural networks for edge detection. https://niceworkshop.org/nice-2023/

We introduced a new feedforward ONN architecture to solve image edge detection with our digital design. This novel architecture proposes an alternative to convolutional filters in the case of image edge detection application. And it will help exploring novel ONN [...]

We are excited to introduce NeurONN’s second ONN integrated circuit (IC) which implements SKONN, a new mixed-signal ONN architecture that separates analog computation and digital propagation. The chip contains 16 neurons, 256 programmable synapses with 5 bits of resolution [...]

EU H2020 NeurONN participated in HiPEAC 2023 Conference! Our PhD student Madeleine Abernot at CNRS-LIRMM presented her work at HiPEAC, #NEUROCOM workshop. Her work in collaboration with A.I.Mergence is on the design and implementation of digital oscillatory neural networks for [...]

We are thrilled about our recent paper publication at Nature Portfolio #Scientific Reports, part of themed collection “Novel hardware and concepts for unconventional computing”.  We used finite element method (technology computer-aided design, TCAD) simulations of VO2 oscillators to explore [...]

Our colleagues from IMSE-CNM, CSIC contributed with two oral lectures at #DCIS 2022 on alternative learning methods as associative memory for ONNs and its interesting performance as a hardware accelerator at solving NP-hard combinatorial optimization problems. Manuel Jiménez Través presented his [...]