International audienceWe study properties of the family of small-world random graphs introduced in Watts & Strogatz (1998), focusing on the spectrum of the normalized graph Laplacian. This spectrum influences the extent to which a signal supported on the vertices of the graph can be simultaneously localized on the graph and in the spectral domain (the surrogate of the frequency domain for signals supported on a graph). This characterization has implications for inferring or interpolating functions supported on such graphs when observations are only available at a subset of nodes. View full abstract
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, di...
New classes of random graphs have recently been shown to exhibit the small world phenomenon - they a...
This chapter contains a brief introduction to complex networks, and in particular to small world and...
International audienceWe study properties of the family of small-world random graphs introduced in W...
Abstract—In applications such as social, energy, transporta-tion, sensor, and neuronal networks, hig...
International audienceSignal processing on graphs is a recent research domain that aims at generaliz...
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra ch...
Analysis of signals defined on complex topologies modeled by graphs is a topic of increasing interes...
International audienceWe propose a new point of view in the study of Fourier analysis on graphs, tak...
We compute spectra of symmetric random matrices describing graphs with general modular structure and...
In this dissertation we study a problem in mathematical physics concerning the eigenvalues of random...
The spectral properties of the Laplacian operator on "small-world" lattices, that is mixtures of un...
Graphs are a central tool in machine learning and information processing as they allow to convenient...
International audienceIn this paper, we look at one of the most crucial ingredient to graph signal p...
International audienceThe graph Laplacian plays an important role in describing the structure of a g...
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, di...
New classes of random graphs have recently been shown to exhibit the small world phenomenon - they a...
This chapter contains a brief introduction to complex networks, and in particular to small world and...
International audienceWe study properties of the family of small-world random graphs introduced in W...
Abstract—In applications such as social, energy, transporta-tion, sensor, and neuronal networks, hig...
International audienceSignal processing on graphs is a recent research domain that aims at generaliz...
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra ch...
Analysis of signals defined on complex topologies modeled by graphs is a topic of increasing interes...
International audienceWe propose a new point of view in the study of Fourier analysis on graphs, tak...
We compute spectra of symmetric random matrices describing graphs with general modular structure and...
In this dissertation we study a problem in mathematical physics concerning the eigenvalues of random...
The spectral properties of the Laplacian operator on "small-world" lattices, that is mixtures of un...
Graphs are a central tool in machine learning and information processing as they allow to convenient...
International audienceIn this paper, we look at one of the most crucial ingredient to graph signal p...
International audienceThe graph Laplacian plays an important role in describing the structure of a g...
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, di...
New classes of random graphs have recently been shown to exhibit the small world phenomenon - they a...
This chapter contains a brief introduction to complex networks, and in particular to small world and...