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nlin.AO2024
Generalization emerges from local optimization in a self-organized learning network
S. Barland, L. Gil
We design and analyze a new paradigm for building supervised learning networks, driven only by local optimization rules without relying on a global error function. Traditional neur…
nlin.AO2023
Self adaptation of networks of non-identical pulse-coupled excitatory and inhibitory oscillators in the presence of distance-related delays to achieve frequency synchronisation
L. Gil
We show that a network of non-identical nodes, with excitable dynamics, pulse-coupled, with coupling delays depending on the Euclidean distance between nodes, is able to adapt the…
nlin.AO2021
Optimally frequency synchronized networks of non identical Kuramoto oscillators
Lionel Gil
Based on a local greedy numerical algorithm, we compute the topology of weighted, directed, and of unlimited extension networks of non identical Kuramoto oscillators which simultan…