2 citations · 2 across the 5 of their papers we have counts for
5 papers
Sparse associative memory based on contextual code learning for disambiguating word senses
Max Raphael Sobroza, Tales Marra, Deok-Hee Kim-Dufor +1
In recent literature, contextual pretrained Language Models (LMs) demonstrated their potential in generalizing the knowledge to several Natural Language Processing (NLP) tasks incl…
Robust Associative Memories Naturally Occuring From Recurrent Hebbian Networks Under Noise
Eliott Coyac, Vincent Gripon, Charlotte Langlais +1
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…
Storing sequences in binary tournament-based neural networks
Xiaoran Jiang, Vincent Gripon, Claude Berrou +1
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…
Learning sparse messages in networks of neural cliques
Behrooz Kamary Aliabadi, Claude Berrou, Vincent Gripon +1
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 ne…
Sparse neural networks with large learning diversity
Vincent Gripon, Claude Berrou
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.…