Marc Lavielle

29 papers A* 1Journal 25Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
A joint analysis proposal of nonlinear longitudinal and time-to-event right-, interval-censored data for modeling pregnancy miscarriage.
Comput. Biol. Medicine
Rolando De la Cruz, Marc Lavielle, Cristian Meza, Vicente Núñez-Antón
2022 J jnl
Using hospital data for monitoring the dynamics of COVID-19 in France.
J. Data Sci. Stat. Vis.
Marc Lavielle
2020 J jnl
Logistic regression with missing covariates - Parameter estimation, model selection and prediction within a joint-modeling framework.
Comput. Stat. Data Anal.
Wei Jiang, Julie Josse, Marc Lavielle, TraumaBase Group
2020 J jnl
f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects models.
Comput. Stat. Data Anal.
Belhal Karimi, Marc Lavielle, Eric Moulines
2019 J jnl
Inheritance and variability of kinetic gene expression parameters in microbial cells: modeling and inference from lineage tree data.
Bioinform.
Aline Marguet, Marc Lavielle, Eugenio Cinquemani
2019 A* conf
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods.
NeurIPS
Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
2019 J jnl
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods.
CoRR
Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
2014 J jnl
An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models.
Stat. Comput.
Marc Lavielle, Cyprien Mbogning
2012 J jnl
Maximum likelihood estimation in discrete mixed hidden Markov models using the SAEM algorithm.
Comput. Stat. Data Anal.
Maud Delattre, Marc Lavielle
2009 — conf
Anatomically Informed Bayesian Model Selection for fMRI Group Data Analysis.
MICCAI (1)
Merlin Keller, Marc Lavielle, Matthieu Perrot, Alexis Roche
2007 J jnl
A parameter expansion version of the SAEM algorithm.
Stat. Comput.
Marc Lavielle, Cristian Meza
2006 J jnl
Are fMRI event-related response constant in time? A model selection answer.
NeuroImage
Sophie Donnet, Marc Lavielle, Jean-Baptiste Poline
2006 J jnl
Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model.
Comput. Stat. Data Anal.
Adeline Samson, Marc Lavielle, France Mentré
2005 J jnl
A statistical approach for array CGH data analysis.
BMC Bioinform.
Franck Picard, Stéphane Robin, Marc Lavielle, Christian Vaisse, Jean-Jacques Daudin
2005 — conf
Blind source separation of noisy mixtures using a semi-parametric approach with application to heavy-tailed signals.
EUSIPCO
Mohamed Sahmoudi, Karim Abed-Meraim, Marc Lavielle, Estelle Kuhn, Philippe Ciblat
2005 J jnl
Maximum likelihood estimation in nonlinear mixed effects models.
Comput. Stat. Data Anal.
Estelle Kuhn, Marc Lavielle
2005 J jnl
Semiparametric estimation of the frequency of unknown periodic functions and its application to laser vibrometry signals.
IEEE Trans. Signal Process.
Marc Lavielle, Céline Lévy-Leduc
2005 J jnl
Using penalized contrasts for the change-point problem.
Signal Process.
Marc Lavielle
2004 — conf
Selection of Temporal Models for Event-Related fMRI.
ISBI
Sophie Donnet, Marc Lavielle, Philippe Ciuciu, Jean-Baptiste Poline
2003 J jnl
Bayesian off-line detection of multiple change-points corrupted by multiplicative noise: application to SAR image edge detection.
Signal Process.
Jean-Yves Tourneret, Michel Doisy, Marc Lavielle
2001 J jnl
An application of MCMC methods for the multiple change-points problem.
Signal Process.
Marc Lavielle, E. Lebarbier
1999 J jnl
Gibbs sampling for parameters estimation and change-points detection in inverse problems. Application to electromagnetic imaging.
Signal Process.
Marc Lavielle, D. Marquez
1999 J jnl
Simulation-based methods for blind maximum-likelihood filter identification.
Signal Process.
Olivier Cappé, Arnaud Doucet, Marc Lavielle, Eric Moulines
1998 J jnl
Optimal segmentation of random processes.
IEEE Trans. Signal Process.
Marc Lavielle
1997 J jnl
A simulated annealing version of the EM algorithm for non-Gaussian deconvolution.
Stat. Comput.
Marc Lavielle, Eric Moulines
1995 J jnl
A stochastic algorithm for parametric and non-parametric estimation in the case of incomplete data.
Signal Process.
Marc Lavielle
1994 J jnl
On two-dimensional spectral realization.
IEEE Trans. Inf. Theory
Fabrice Gamboa, Marc Lavielle
1993 J jnl
Bayesian deconvolution of Bernoulli-Gaussian processes.
Signal Process.
Marc Lavielle
1993 J jnl
Detection of changes in the spectrum of a multidimensional process.
IEEE Trans. Signal Process.
Marc Lavielle