Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems. - Magalie Fromont; Béatrice Laurent; Matthieu Lerasle; Patricia Reynaud-Bouret (COLT, 2012)

Nonparametric Estimation of the Division Rate of a Size-Structured Population. - Marie Doumic; M. Hoffmann; Patricia Reynaud-Bouret; Vincent Rivoirard (SIAM J. Numer. Anal., 2012)

Inference of functional connectivity in Neurosciences via Hawkes processes. - Patricia Reynaud-Bouret; Vincent Rivoirard; Christine Tuleau-Malot (GlobalSIP, 2013)

Multiple Tests Based on a Gaussian Approximation of the Unitary Events Method with Delayed Coincidence Count. - Christine Tuleau-Malot; Amel Rouis; Franck Grammont; Patricia Reynaud-Bouret (Neural Comput., 2014)

Microscopic approach of a time elapsed neural model. - Julien Chevallier; María J. Cáceres; Marie Doumic; Patricia Reynaud-Bouret (CoRR, 2015)

Genomic transcription regulatory element location analysis via poisson weighted lasso. - Xin Jiang Hunt; Patricia Reynaud-Bouret; Vincent Rivoirard; Laure Sansonnet; Rebecca Willett (SSP, 2016)

Surrogate Data Methods Based on a Shuffling of the Trials for Synchrony Detection: The Centering Issue. - Mélisande Albert; Yann Bouret; Magalie Fromont; Patricia Reynaud-Bouret (Neural Comput., 2016)

Large scale Lasso with windowed active set for convolutional spike sorting. - Laurent Dragoni; Rémi Flamary; Karim Lounici; Patricia Reynaud-Bouret (CoRR, 2019)

A Data-Dependent Weighted LASSO Under Poisson Noise. - Xin Jiang Hunt; Patricia Reynaud-Bouret; Vincent Rivoirard; Laure Sansonnet; Rebecca Willett (IEEE Trans. Inf. Theory, 2019)

Event-Scheduling Algorithms with Kalikow Decomposition for Simulating Potentially Infinite Neuronal Networks. - Tien Cuong Phi; Alexandre Muzy; Patricia Reynaud-Bouret (SN Comput. Sci., 2020)

Scalability of Large Neural Network Simulations via Activity Tracking With Time Asynchrony and Procedural Connectivity. - Cyrille Mascart; Gilles Scarella; Patricia Reynaud-Bouret; Alexandre Muzy (Neural Comput., 2022)

On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm. - Julien Aubert; Luc Lehéricy; Patricia Reynaud-Bouret (ICML, 2023)

Efficient Simulation of Sparse Graphs of Point Processes. - Cyrille Mascart; David R. C. Hill; Alexandre Muzy; Patricia Reynaud-Bouret (ACM Trans. Model. Comput. Simul., 2023)

Kalikow decomposition for counting processes with stochastic intensity and application to simulation algorithms. - Tien Cuong Phi; Eva Löcherbach; Patricia Reynaud-Bouret (J. Appl. Probab., 2023)

Provable local learning rule by expert aggregation for a Hawkes network. - Sophie Jaffard; Samuel Vaiter; Alexandre Muzy; Patricia Reynaud-Bouret (AISTATS, 2024)

Model selection for behavioral learning data and applications to contextual bandits. - Julien Aubert; Louis Köhler; Luc Lehéricy; Giulia Mezzadri; Patricia Reynaud-Bouret (AISTATS, 2025)

Spiking Neural Models for Decision-Making Tasks with Learning. - Sophie Jaffard; Giulia Mezzadri; Patricia Reynaud-Bouret; Etienne Tanré (CoRR, 2025)