45 citations · 100 across the 29 of their papers we have counts for
4 papers · 1 filter
Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation
Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe +1
Transfer learning using deep neural networks as feature extractors has become increasingly popular over the past few years. It allows to obtain state-of-the-art accuracy on dataset…
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…
SimiNet: a Novel Method for Quantifying Brain Network Similarity
Ahmad Mheich, Mahmoud Hassan, Mohamad Khalil +3
Quantifying the similarity between two networks is critical in many applications. A number of algorithms have been proposed to compute graph similarity, mainly based on the propert…
Learning Local Receptive Fields and their Weight Sharing Scheme on Graphs
Jean-Charles Vialatte, Vincent Gripon, Gilles Coppin
We propose a simple and generic layer formulation that extends the properties of convolutional layers to any domain that can be described by a graph. Namely, we use the support of…