International audienceAn original architecture of oriented sparse neural networks that enables the introduction of sequentiality in associative memories is proposed in this paper. This architecture can be regarded as a generalization of a recently proposed non oriented binary network based on cliques. Using a limited neuron resource, the network is able to learn very long sequences and to retrieve them only from the knowledge of some consecutive symbols
International audienceAssociative memories are devices that are able to learn messages and to retrie...
Auto-associative memories store a set of patterns and retrieve them by resorting to a part of their ...
A crucial step towards the representation of structured, symbolic knowledge in a connectionist syste...
International audienceAn original architecture of oriented sparse neural networks that enables the i...
Sequential structure imposed by the forward linear progression of time is omnipresent in all cogniti...
Abstract—An extension to a recently introduced architecture of clique-based neural networks is prese...
International audienceAssociative memories are data structures addressed using part of the content r...
International audienceCoded recurrent neural networks with three levels of sparsity are introduced. ...
In sequence learning studies we can distinguish two fundamental approaches: general-regularity lea...
International audienceAssociative memories are devices that are able to learn messages and to retrie...
Auto-associative memories store a set of patterns and retrieve them by resorting to a part of their ...
A crucial step towards the representation of structured, symbolic knowledge in a connectionist syste...
International audienceAn original architecture of oriented sparse neural networks that enables the i...
Sequential structure imposed by the forward linear progression of time is omnipresent in all cogniti...
Abstract—An extension to a recently introduced architecture of clique-based neural networks is prese...
International audienceAssociative memories are data structures addressed using part of the content r...
International audienceCoded recurrent neural networks with three levels of sparsity are introduced. ...
In sequence learning studies we can distinguish two fundamental approaches: general-regularity lea...
International audienceAssociative memories are devices that are able to learn messages and to retrie...
Auto-associative memories store a set of patterns and retrieve them by resorting to a part of their ...
A crucial step towards the representation of structured, symbolic knowledge in a connectionist syste...