277 citations · 343 across the 4 of their papers we have counts for
4 papers
Compressive Embedding and Visualization using Graphs
Johan Paratte, Nathanaël Perraudin, Pierre Vandergheynst
Visualizing high-dimensional data has been a focus in data analysis communities for decades, which has led to the design of many algorithms, some of which are now considered refere…
Fast Eigenspace Approximation using Random Signals
Johan Paratte, Lionel Martin
We focus in this work on the estimation of the first eigenvectors of any graph Laplacian using filtering of Gaussian random signals. We prove that we only need such signals…
Graph-based denoising for time-varying point clouds
Yann Schoenenberger, Johan Paratte, Pierre Vandergheynst
Noisy 3D point clouds arise in many applications. They may be due to errors when constructing a 3D model from images or simply to imprecise depth sensors. Point clouds can be given…
GSPBOX: A toolbox for signal processing on graphs
Nathanaël Perraudin, Johan Paratte, David Shuman +4
This document introduces the Graph Signal Processing Toolbox (GSPBox) a framework that can be used to tackle graph related problems with a signal processing approach. It explains t…