8 citations · 36 across the 25 of their papers we have counts for
3 papers · 1 filter
Convolutional neural networks on irregular domains based on approximate vertex-domain translations
Bastien Pasdeloup, Vincent Gripon, Jean-Charles Vialatte +2
We propose a generalization of convolutional neural networks (CNNs) to irregular domains, through the use of a translation operator on a graph structure. In regular settings such a…
A neighborhood-preserving translation operator on graphs
Bastien Pasdeloup, Vincent Gripon, Jean-Charles Vialatte +2
In this paper, we introduce translation operators on graphs. Contrary to spectrally-defined translations in the framework of graph signal processing, our operators mimic neighborho…
Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality Reduction
Mathilde Ménoret, Nicolas Farrugia, Bastien Pasdeloup +1
Graph Signal Processing (GSP) is a promising framework to analyze multi-dimensional neuroimaging datasets, while taking into account both the spatial and functional dependencies be…