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pro vyhledávání: '"Berrou, Claude"'
Diversity is a concept of prime importance in almost all disciplines based on information processing. In telecommunications, for example, spatial, temporal, and frequency diversity, as well as redundant coding, are fundamental concepts that have enab
Externí odkaz:
http://arxiv.org/abs/2407.12599
In recent literature, contextual pretrained Language Models (LMs) demonstrated their potential in generalizing the knowledge to several Natural Language Processing (NLP) tasks including supervised Word Sense Disambiguation (WSD), a challenging proble
Externí odkaz:
http://arxiv.org/abs/1911.06415
The brain is a noisy system subject to energy constraints. These facts are rarely taken into account when modelling artificial neural networks. In this paper, we are interested in demonstrating that those factors can actually lead to the appearance o
Externí odkaz:
http://arxiv.org/abs/1709.08367
An extension to a recently introduced architecture of clique-based neural networks is presented. This extension makes it possible to store sequences with high efficiency. To obtain this property, network connections are provided with orientation and
Externí odkaz:
http://arxiv.org/abs/1409.0334
An extension to a recently introduced binary neural network is proposed in order to allow the learning of sparse messages, in large numbers and with high memory efficiency. This new network is justified both in biological and informational terms. The
Externí odkaz:
http://arxiv.org/abs/1208.4009
Autor:
Gripon, Vincent, Berrou, Claude
Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages, much smaller than the number of available neurons. The second one is provided by a particular coding rule, acting as a l
Externí odkaz:
http://arxiv.org/abs/1102.4240
Akademický článek
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Autor:
Hassan, Mahmoud, Benquet, Pascal, Biraben, Arnaud, Berrou, Claude, Dufor, Olivier, Wendling, Fabrice
Publikováno v:
In Cortex December 2015 73:276-288
