Processus stochastiques

Les données collectées sont systématiquement soumises à des perturbations de diverses natures, depuis le bruit de mesure de capteurs jusqu’aux erreurs de saisie.

In this talk I will briefly recall the framework of local weak limits of finite graphs introduced by I. Benjamini and O. Schramm

Motivated by Krioukov et al.'s model of random hyperbolic graphs for real-world networks, and inspired by the analysis of a dynamic model of graphs in Euclidean space by Peres et al., we introduce a

Combinatorial maps are a model of discrete geometry: they are surfaces made by gluing  polygons along their sides, or equivalently, graphs drawn on surfaces. In this talk, I'll focus on the study of

A matching in a graph is a set of edges that do not share endpoints. Developing algorithms that find large matchings is an important problem. An algorithm is said to be online if it has to construct

We consider a sequence of Poisson cluster point processes...

Cost is a natural invariant associated to group actions and invariant point processes on symmetric spaces (such as Euclidean space and hyperbolic space). Informally, it measures how difficult it is to

We consider homogeneous real random functions defined on the Euclidean space.

We study approximation problems in reproducing kernel Hilbert spaces (RKHS) using random nodes.

The work is motivated by car-sharing systems like Autolib’ in Paris (2011-2017) where, for charging, electric cars are parked in small capacity nodes.

We introduce spatial regulation properties for stationary spatial point processes and develop...

A Hawkes process on the real line is a point process whose intensity function at time is a functional of its past activity before time.