1 code implementation • 22 Oct 2020 • Benjamin Ricaud, Nicolas Aspert, Volodymyr Miz
Studying real-world networks such as social networks or web networks is a challenge.
no code implementations • 19 Oct 2020 • Alexandru Mocanu, Benjamin Ricaud, Milos Cernak
Music source separation represents the task of extracting all the instruments from a given song.
1 code implementation • 17 Feb 2020 • Volodymyr Miz, Joëlle Hanna, Nicolas Aspert, Benjamin Ricaud, Pierre Vandergheynst
In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia.
Social and Information Networks Computers and Society
no code implementations • 25 Sep 2019 • Helena Peic Tukuljac, Benjamin Ricaud, Nicolas Aspert, Pierre Vandergheynst
This layer aims at being the input layer of convolutional neural networks for audio applications.
1 code implementation • 20 Mar 2019 • Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud, Pierre Vandergheynst
It makes the parsing and extraction of relevant information cumbersome.
2 code implementations • 22 Jan 2019 • Volodymyr Miz, Benjamin Ricaud, Kirell Benzi, Pierre Vandergheynst
We define an anomaly as a localized increase in temporal activity in a cluster of nodes.
1 code implementation • 1 Oct 2017 • Volodymyr Miz, Kirell Benzi, Benjamin Ricaud, Pierre Vandergheynst
The model exploits collective effect of the dynamics to discover events.
no code implementations • 5 May 2017 • Francesco Grassi, Andreas Loukas, Nathanaël Perraudin, Benjamin Ricaud
An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph.
no code implementations • 21 Jun 2016 • Francesco Grassi, Nathanael Perraudin, Benjamin Ricaud
Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph.
no code implementations • 10 Mar 2016 • Nathanael Perraudin, Benjamin Ricaud, David Shuman, Pierre Vandergheynst
Accordingly, we suggest a new way to incorporate a notion of locality, and develop local uncertainty principles that bound the concentration of the analysis coefficients of each atom of a localized graph spectral filter frame in terms of quantities that depend on the local structure of the graph around the center vertex of the given atom.