4 citations · 6 across the 5 of their papers we have counts for
9 papers
Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities
Yassine El Ouahidi, Lucas Drumetz, Giulia Lioi +3
BCI Motor Imagery datasets usually are small and have different electrodes setups. When training a Deep Neural Network, one may want to capitalize on all these datasets to increase…
Pruning Graph Convolutional Networks to select meaningful graph frequencies for fMRI decoding
Yassine El Ouahidi, Hugo Tessier, Giulia Lioi +3
Graph Signal Processing is a promising framework to manipulate brain signals as it allows to encompass the spatial dependencies between the activity in regions of interest in the b…
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification
Myriam Bontonou, Nicolas Farrugia, Vincent Gripon
It is very common to face classification problems where the number of available labeled samples is small compared to their dimension. These conditions are likely to cause underdete…
Gradients of Connectivity as Graph Fourier Bases of Brain Activity
Giulia Lioi, Vincent Gripon, Abdelbasset Brahim +2
The application of graph theory to model the complex structure and function of the brain has shed new light on its organization and function, prompting the emergence of network neu…
Efficient Hardware Implementation of Incremental Learning and Inference on Chip
Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia +2
In this paper, we tackle the problem of incrementally learning a classifier, one example at a time, directly on chip. To this end, we propose an efficient hardware implementation o…
Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging
Yusuf Pilavci, Nicolas Farrugia
Graph Signal Processing has become a very useful framework for signal operations and representations defined on irregular domains. Exploiting transformations that are defined on gr…