173 citations · 380 across the 27 of their papers we have counts for
29 papers
Separation rates for the detection of synchronization of interacting point processes in a mean field frame. Application to neuroscience
Josué Tchouanti, Éva Löcherbach, Patricia Reynaud-Bouret +1
Permutation tests have been proposed by Albert et al. (2015) to detect dependence between point processes, modeling in particular spike trains, that is the time occurrences of acti…
Non-asymptotic statistical test of the diffusion coefficient of stochastic differential equations
Anna Melnykova, Patricia Reynaud-Bouret, Adeline Samson
We develop several statistical tests of the determinant of the diffusion coefficient of a stochastic differential equation, based on discrete observations on a time interval $[0,T]…
On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
Julien Aubert, Luc Lehéricy, Patricia Reynaud-Bouret
When fitting the learning data of an individual to algorithm-like learning models, the observations are so dependent and non-stationary that one may wonder what the classical Maxim…
Provable local learning rule by expert aggregation for a Hawkes network
Sophie Jaffard, Samuel Vaiter, Alexandre Muzy +1
We propose a simple network of Hawkes processes as a cognitive model capable of learning to classify objects. Our learning algorithm, named HAN for Hawkes Aggregation of Neurons, i…
Neural Coding as a Statistical Testing Problem
Guilherme Ost, Patricia Reynaud-Bouret
We take the testing perspective to understand what the minimal discrimination time between two stimuli is for different types of rate coding neurons. Our main goal is to describe t…
Sliding window strategy for convolutional spike sorting with Lasso : Algorithm, theoretical guarantees and complexity
Laurent Dragoni, Rémi Flamary, Karim Lounici +1
Spike sorting is a class of algorithms used in neuroscience to attribute the time occurences of particular electric signals, called action potential or spike, to neurons. We rephra…