Add to ORKGWe provide a general bound on the Wasserstein distance between two arbitrary distributions of sequences of Bernoulli random variables. The bound is in terms of a mixing quantity for the Glauber dynamics of one of the sequences, and a simple expectation of the other. The result is applied to estimate, with explicit error, expectations of functions of random vectors for some Ising models and exponential random graphs in “high temperature” regimes
Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wa...
We provide a general steady-state diffusion approximation result which bounds the Wasserstein distan...
International audienceIn this paper, we introduce a Wasserstein-type distance on the set of the prob...
We provide a general bound on the Wasserstein distance between two arbitrary distributions of sequen...
This preprint corresponds to the third section of https://arxiv.org/abs/1601.03301. The main result ...
28 pagesIn a spirit close to classical Stein's method, we introduce a new technique to derive first ...
In this thesis we study the mixing times of Markov chains, e.g., therate of convergence of Markov ch...
An upper bound is given for the mean square Wasserstein distance between the empirical measure of a ...
We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze ...
We analyze the mixing time of a natural local Markov chain (the Glauber dynamics) on configurations...
This paper deals with suitable quantifications in approximating a probability measure by an “empiric...
We derive central limit theorems for the Wasserstein distance between the empirical distributions of...
Abstract. Let µN be the empirical measure associated to a N-sample of a given probability distributi...
In this paper, the Glauber dynamics for the Ising model on the complete multipartite graph $K_{np_1,...
We estimate the Wasserstein type distance between two continuous distributions F and G on R such tha...
Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wa...
We provide a general steady-state diffusion approximation result which bounds the Wasserstein distan...
International audienceIn this paper, we introduce a Wasserstein-type distance on the set of the prob...
We provide a general bound on the Wasserstein distance between two arbitrary distributions of sequen...
This preprint corresponds to the third section of https://arxiv.org/abs/1601.03301. The main result ...
28 pagesIn a spirit close to classical Stein's method, we introduce a new technique to derive first ...
In this thesis we study the mixing times of Markov chains, e.g., therate of convergence of Markov ch...
An upper bound is given for the mean square Wasserstein distance between the empirical measure of a ...
We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze ...
We analyze the mixing time of a natural local Markov chain (the Glauber dynamics) on configurations...
This paper deals with suitable quantifications in approximating a probability measure by an “empiric...
We derive central limit theorems for the Wasserstein distance between the empirical distributions of...
Abstract. Let µN be the empirical measure associated to a N-sample of a given probability distributi...
In this paper, the Glauber dynamics for the Ising model on the complete multipartite graph $K_{np_1,...
We estimate the Wasserstein type distance between two continuous distributions F and G on R such tha...
Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wa...
We provide a general steady-state diffusion approximation result which bounds the Wasserstein distan...
International audienceIn this paper, we introduce a Wasserstein-type distance on the set of the prob...