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Trail formation based on directed pheromone deposition.

• Emmanuel Boissard, Pierre Degond, Sebastien Motsch
• Journal of mathematical biology
• 2013

We propose an Individual-Based Model of ant-trail formation. The ants are modeled as self-propelled particles which deposit directed pheromone particles and interact with them through alignment interaction. The directed pheromone particles intend to model pieces of trails, while the alignment interaction translates the tendency for an ant to follow a trail… (More)

Distribution’s template estimate with Wasserstein metrics

• Emmanuel Boissard, Thibaut Le Gouic, Jean-Michel Loubes, Paul Sabatier
• 2017

In this paper we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random… (More)

On the Mean Speed of Convergence of Empirical and Occupation Measures in Wasserstein Distance

• EMMANUEL BOISSARD
• 2012

In this work, we provide non-asymptotic bounds for the average speed of convergence of the empirical measure in the law of large numbers, in Wasserstein distance. We also consider occupation measures of ergodic Markov chains. One motivation is the approximation of a probability measure by nitely supported measures (the quantization problem). It is found… (More)

Ornstein-uhlenbeck Pinball: I. Poincaré Inequalities in a Punctured Domain

• EMMANUEL BOISSARD, PATRICK CATTIAUX, LAURENT MICLO
• 2013

In this paper we study the Poincaré constant for the Gaussian measure restricted to D = R − B(y, r) where B(y, r) denotes the Euclidean ball with center y and radius r, and d ≥ 2. We also study the case of the l ball (the hypercube). This is the first step in the study of the asymptotic behavior of a d-dimensional Ornstein-Uhlenbeck process in the presence… (More)

Diffusivity of a random walk on random walks

• Emmanuel Boissard, Serge Cohen, Thibault Espinasse, James Norris
• Random Struct. Algorithms
• 2015

We consider a random walk ( Z (1) n , · · · , Z n ) ∈ Z with the constraint that each coordinate of the walk is at distance one from the following one. In this paper, we show that this random walk is slowed down by a variance factor σ K = 2 K+2 with respect to the case of the classical simple random walk without constraint.

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