13 citations · 18 across the 8 of their papers we have counts for
11 papers
Controlling the latency in temporal coded spiking models for neuromorphic datasets
Alban Gattepaille, Alexandre Muzy
Exploiting temporal information in datasets with high temporal dependencies (such as spoken keyword recognition) by spiking models is still an open problem. Promising frameworks in…
Design and Analysis of Temporal Representations in Neural Networks
Alban Colas-Gattepaille, Alexandre Muzy
The ability to represent temporal information is often hypothesized to underlie the efficiency and learning capabilities of biological neural networks. This motivates the developme…
Towards a faithful stochastic model for brain digital twins
Abdelhamid Rouatbi, Alexandre Muzy, Eugene Syriani
Twinning the brain means reproducing its electrical activity with fidelity. This activity arises from many neuronal mechanisms across several scales, from a single neuron to whole…
From Brain Models to Executable Digital Twins: Execution Semantics and Neuro-Neuromorphic Systems
Alexandre Muzy
Brain digital twins aim to provide faithful, individualized computational representations of brains as dynamical systems, enabling mechanistic understanding and supporting predicti…
Modeling and Simulation Based Engineering in the Context of Cyber-Physical Systems
Alexandre Muzy
Cyber-Physical Systems (CPS) produce behavior through execution on substrates coupling computation with physical processes. However, usual engineering approaches do not treat execu…
Delay Neural Networks (DeNN) for exploiting temporal information in event-based datasets
Alban Gattepaille, Alexandre Muzy
In Deep Neural Networks (DNN) and Spiking Neural Networks (SNN), the information of a neuron is computed based on the sum of the amplitudes (weights) of the electrical potentials r…