Maximum likelihood estimation in discrete mixed hidden Markov models using the SAEM algorithm. - Maud Delattre; Marc Lavielle (Comput. Stat. Data Anal., 2012)

Two-dimensional segmentation for analyzing Hi-C data. - Céline Lévy-Leduc; Maud Delattre; Tristan Mary-Huard; Stéphane Robin (Bioinform., 2014)

Inference for partially observed epidemic dynamics guided by Kalman filtering techniques. - Romain Narci; Maud Delattre; Catherine Larédo; Elisabeta Vergu (Comput. Stat. Data Anal., 2021)

Efficient preconditioned stochastic gradient descent for estimation in latent variable models. - Charlotte Baey; Maud Delattre; Estelle Kuhn; Jean-Benoist Leger; Sarah Lemler (ICML, 2023)

Modeling soybean growth: A mixed model approach. - Maud Delattre; Yusuke Toda; Jessica Tressou; Hiroyoshi Iwata (PLoS Comput. Biol., 2024)

Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. - Marion Naveau; Guillaume Kon Kam King; Renaud Rincent; Laure Sansonnet; Maud Delattre (Stat. Comput., 2024)

Correction to: Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. - Marion Naveau; Guillaume Kon Kam King; Renaud Rincent; Laure Sansonnet; Maud Delattre (Stat. Comput., 2024)