16 citations · 28 across the 7 of their papers we have counts for
9 papers
Parametric Rectified Power Sigmoid Units: Learning Nonlinear Neural Transfer Analytical Forms
Abdourrahmane Mahamane Atto, Sylvie Galichet, Dominique Pastor +1
The paper proposes representation functionals in a dual paradigm where learning jointly concerns both linear convolutional weights and parametric forms of nonlinear activation func…
Decentralized Clustering on Compressed Data without Prior Knowledge of the Number of Clusters
Elsa Dupraz, Dominique Pastor, François-Xavier Socheleau
In sensor networks, it is not always practical to set up a fusion center. Therefore, there is need for fully decentralized clustering algorithms. Decentralized clustering algorithm…
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…
Decentralized Clustering based on Robust Estimation and Hypothesis Testing
Dominique Pastor, Elsa Dupraz, François-Xavier Socheleau
This paper considers a network of sensors without fusion center that may be difficult to set up in applications involving sensors embedded on autonomous drones or robots. In this c…
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…