Keywords: Machine Learning & Hidden Markov Chains ; Sequential Monte Carlo for on-line estimation; Stochastic volatility models
Estimation of the Order of Non-Parametric Hidden Markov Models using the Singular Values of an Integral Operator, with M. Du Roy de Chaumaray, M.P. Etienne and M. Marbac , 2024: accepted in Journal of Machine Learning Research, ArXiv
Kernel Smoothing Conditional Particle filter with Ancestor Sampling, with F. Navarro, 2024 : IEEE Transactions on Signal Processing
Investigating swimming technical skills by a double partition clustering of multivariate functional data allowing for dimension selection, with A. Bouvet and M. Marbac, 2023 : Annals of Applied Statistics, ArXiv
Parametric estimation of hidden Markov models by least squares type estimation and deconvolution (with C. Chesneau et F. Navarro), 2022: Statistical Papers
Contrast estimation for noisy obervations of diffusion processes via closed-form density expansions (with F. Navarro), 2021: Statistical Inference for Stochastic processes
Nonparametric estimation in a regression model with additive and multiplicative noise (with C. Chesneau, J. Kou, F. Navarro), 2020: Journal of Computational and Applied Mathematics
Adaptive density estimation on bounded domains (with K. Bertin and N. Klutchnikoff), 2019 : Annales de l'Institut Henri Poincaré (B) , ArXiv
Analysis, detection and correction of misspecified discrete time state space models, (with F. Patras), 2018 : Journal Of Computational and Applied Mathematics , ArXiv
Parametric inference of autoregressive heteroscedastic models with error in variables (with F. Pelgrin), 2017 : Statistics & Probability Letters, ArXiv
Parametric estimation of hidden stochastic models by deconvolution and contrast minimization: application to the stochastic volatility models, 2013 : Metrika, ArXiv.
L'apprentissage profond (2018), a French translation of Deep Learning, Florent Massot & Quantmetry. "The first book on deep learning translated using deep learning". Editor and lead traducer, with I. Goodfellow, Y. Bengio, A. Courville, F. Navarro, S. El Kolei, B. Guedj, C. Chesneau, N. Bousquet .
Pre-print:
Investigating the estimation of latent variable models with M. Marbac
On-line learning state space models by adaptive Kalman filter in the presence of concept drift with F. Patras
Signature methods for study complications of patients suffering from epilepsy with Y. Youssfi
Propagation of initial error on the parameters for linear and Gaussian state-space models : ArXiv
Géométrie des matrices de covariance pour le traitement des signaux radars : Hal
September 2022-present: Antoine Bouvet Analyzing inertial swimming data for automatically monitoring athlete's activity during training. Jointly supervised with M. Marbac (CREST-Ensai) and Nicolas Bideau (M2S)
Estimation des modèles à volatilité stochastique par filtrage et déconvolution : Manuscrit