Add to ORKGWe studied competitive learning dynamics in different time scale regimes of learning. By first assum...
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain proc...
International audienceIn this paper, an original dynamical system derived from dynamic neural fields...
International audienceAs introduced by Amari, dynamic neural fields (DNF) are a mathematical formali...
International audienceIn this paper, dynamic neural fields are used to develop key features of a cort...
International audienceDespite being successfully used in the design of various biologically-inspired...
International audienceThis work provides theoretical conditions guaranteeing that a self-organizing ...
Dans ce manuscrit nous proposons une architecture neuronale d'inspiration corticale, capable de déve...
International audienceWe present in this paper an original neural architecture based on a Dynamic Se...
In this work we propose a cortically inspired neural architecture capable of developping an emergent...
L'objectif de ce travail est de modéliser la formation, la maintenance et la réorganisation des cart...
Dynamic Field Theory (DFT) is an established framework for modeling embodied cognition. In DFT, elem...
International audienceThis paper presents a multi-map joint self-organizing architecture able to rep...
We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which s...
Abstract:- We propose a new self-organizing neural model that considers a dynamic topology among neu...
We studied competitive learning dynamics in different time scale regimes of learning. By first assum...
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain proc...
International audienceIn this paper, an original dynamical system derived from dynamic neural fields...
International audienceAs introduced by Amari, dynamic neural fields (DNF) are a mathematical formali...
International audienceIn this paper, dynamic neural fields are used to develop key features of a cort...
International audienceDespite being successfully used in the design of various biologically-inspired...
International audienceThis work provides theoretical conditions guaranteeing that a self-organizing ...
Dans ce manuscrit nous proposons une architecture neuronale d'inspiration corticale, capable de déve...
International audienceWe present in this paper an original neural architecture based on a Dynamic Se...
In this work we propose a cortically inspired neural architecture capable of developping an emergent...
L'objectif de ce travail est de modéliser la formation, la maintenance et la réorganisation des cart...
Dynamic Field Theory (DFT) is an established framework for modeling embodied cognition. In DFT, elem...
International audienceThis paper presents a multi-map joint self-organizing architecture able to rep...
We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which s...
Abstract:- We propose a new self-organizing neural model that considers a dynamic topology among neu...
We studied competitive learning dynamics in different time scale regimes of learning. By first assum...
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain proc...
International audienceIn this paper, an original dynamical system derived from dynamic neural fields...