Marc Lavielle - researchr alias

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Viewing Publication 1 - 23 from 23

2022

Using hospital data for monitoring the dynamics of COVID-19 in FranceMarc Lavielle. jdssv, 2(7):46-62, 2022. [doi]

2020

Logistic regression with missing covariates - Parameter estimation, model selection and prediction within a joint-modeling frameworkWei Jiang, Julie Josse, Marc Lavielle, TraumaBase Group. csda, 145:106907, 2020. [doi]

f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects modelsBelhal Karimi, Marc Lavielle, Eric Moulines. csda, 141:123-138, 2020. [doi]

2019

On the Global Convergence of (Fast) Incremental Expectation Maximization MethodsBelhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle. nips 2019: 2833-2843 [doi]

Inheritance and variability of kinetic gene expression parameters in microbial cells: modeling and inference from lineage tree dataAline Marguet, Marc Lavielle, Eugenio Cinquemani. bioinformatics, 35(14), 2019. [doi]

2014

An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects modelsMarc Lavielle, Cyprien Mbogning. sac, 24(5):693-707, 2014. [doi]

2012

Maximum likelihood estimation in discrete mixed hidden Markov models using the SAEM algorithmMaud Delattre, Marc Lavielle. csda, 56(6):2073-2085, 2012. [doi]

2009

Anatomically Informed Bayesian Model Selection for fMRI Group Data AnalysisMerlin Keller, Marc Lavielle, Matthieu Perrot, Alexis Roche. miccai 2009: 450-457 [doi]

2007

A parameter expansion version of the SAEM algorithmMarc Lavielle, Cristian Meza. sac, 17(2):121-130, 2007. [doi]

2006

Are fMRI event-related response constant in time? A model selection answerSophie Donnet, Marc Lavielle, Jean-Baptiste Poline. neuroimage, 31(3):1169-1176, 2006. [doi]

Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics modelAdeline Samson, Marc Lavielle, France Mentré. csda, 51(3):1562-1574, 2006. [doi]

2005

Using penalized contrasts for the change-point problemMarc Lavielle. sigpro, 85(8):1501-1510, 2005. [doi]

Semiparametric estimation of the frequency of unknown periodic functions and its application to laser vibrometry signalsMarc Lavielle, Céline Lévy-Leduc. tsp, 53(7):2306-2314, 2005. [doi]

A statistical approach for array CGH data analysisFranck Picard, Stéphane Robin, Marc Lavielle, Christian Vaisse, Jean-Jacques Daudin. bmcbi, 6:27, 2005. [doi]

2004

Selection of Temporal Models for Event-Related fMRISophie Donnet, Marc Lavielle, Philippe Ciuciu, Jean-Baptiste Poline. isbi 2004: 992-995

2003

Bayesian off-line detection of multiple change-points corrupted by multiplicative noise: application to SAR image edge detectionJean-Yves Tourneret, Michel Doisy, Marc Lavielle. sigpro, 83(9):1871-1887, 2003. [doi]

1999

Simulation-based methods for blind maximum-likelihood filter identificationOlivier Cappé, Arnaud Doucet, Marc Lavielle, Eric Moulines. sigpro, 73(1-2):3-25, 1999. [doi]

Gibbs sampling for parameters estimation and change-points detection in inverse problems. Application to electromagnetic imagingMarc Lavielle, D. Marquez. sigpro, 78(3):349-362, 1999. [doi]

1998

Optimal segmentation of random processesMarc Lavielle. tsp, 46(5):1365-1373, 1998. [doi]

1997

A simulated annealing version of the EM algorithm for non-Gaussian deconvolutionMarc Lavielle, Eric Moulines. sac, 7(4):229-236, 1997. [doi]

1995

A stochastic algorithm for parametric and non-parametric estimation in the case of incomplete dataMarc Lavielle. sigpro, 42(1):3-17, 1995. [doi]

1993

Detection of changes in the spectrum of a multidimensional processMarc Lavielle. tsp, 41(2):742-749, 1993. [doi]

Bayesian deconvolution of Bernoulli-Gaussian processesMarc Lavielle. sigpro, 33(1):67-79, 1993. [doi]

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