45 citations · 65 across the 15 of their papers we have counts for
20 papers
Emergence of Common Noise: Quantitative Conditional Propagation of Chaos
Vlad Bally, Eva Löcherbach
We study a dynamical invariance principle for interacting particle systems with mean-field interactions and common noise emerging through a collective stochastic perturbation. The…
Weak conditional propagation of chaos for systems of interacting particles with nearly stable jumps
Eva Löcherbach, Dasha Loukianova, Elisa Marini
We consider a system of interacting particles, described by SDEs driven by Poisson random measures, where the coefficients depend on the empirical measure of the system. Every…
A new look at perfect simulation for chains with infinite memory
Emilio De Santis, Kádmo Laxa, Eva Löcherbach
In this article we introduce two new perfect simulation algorithms for chains with infinite memory. Both algorithms belong to the coupling of past procedures. The novelty of our ap…
Inferring the dependence graph density of binary graphical models in high dimension
Julien Chevallier, Eva Löcherbach, Guilherme Ost
We consider a system of binary interacting chains describing the dynamics of a group of components that, at each time unit, either send some signal to the others or remain sile…
Fluctuations for mean field limits of interacting systems of spiking neurons
Eva Löcherbach
We consider a system of neurons, each spiking randomly with rate depending on its membrane potential. When a neuron spikes, its potential is reset to and all other neurons…
Strong error bounds for the convergence to its mean field limit for systems of interacting neurons in a diffusive scaling
Xavier Erny, Eva Löcherbach, Dasha Loukianova
We consider the stochastic system of interacting neurons introduced in De Masi et al. (2015) and in Fournier and Löcherbach (2016) and then further studied in Erny, Löcherbach and…