207 citations · 516 across the 63 of their papers we have counts for
6 papers · 1 filter
Associative Memories to Accelerate Approximate Nearest Neighbor Search
Vincent Gripon, Matthias Löwe, Franck Vermet
Nearest neighbor search is a very active field in machine learning for it appears in many application cases, including classification and object retrieval. In its canonical version…
Neighborhood-Preserving Translations on Graphs
Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte +1
In many domains (e.g. Internet of Things, neuroimaging) signals are naturally supported on graphs. These graphs usually convey information on similarity between the values taken by…
Generalizing the Convolution Operator to extend CNNs to Irregular Domains
Jean-Charles Vialatte, Vincent Gripon, Grégoire Mercier
Convolutional Neural Networks (CNNs) have become the state-of-the-art in supervised learning vision tasks. Their convolutional filters are of paramount importance for they allow to…
Characterization and Inference of Graph Diffusion Processes from Observations of Stationary Signals
Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier +2
Many tools from the field of graph signal processing exploit knowledge of the underlying graph's structure (e.g., as encoded in the Laplacian matrix) to process signals on the grap…
Graph reconstruction from the observation of diffused signals
Bastien Pasdeloup, Michael Rabbat, Vincent Gripon +2
Signal processing on graphs has received a lot of attention in the recent years. A lot of techniques have arised, inspired by classical signal processing ones, to allow studying si…
Towards a characterization of the uncertainty curve for graphs
Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier +1
Signal processing on graphs is a recent research domain that aims at generalizing classical tools in signal processing, in order to analyze signals evolving on complex domains. Suc…