181 citations · 661 across the 28 of their papers we have counts for
3 papers · 1 filter
Large Scale Graph Learning from Smooth Signals
Vassilis Kalofolias, Nathanaël Perraudin
Graphs are a prevalent tool in data science, as they model the inherent structure of the data. They have been used successfully in unsupervised and semi-supervised learning. Typica…
A Time-Vertex Signal Processing Framework
Francesco Grassi, Andreas Loukas, Nathanaël Perraudin +1
An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related…
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…