Pierre Latouche

mardi 13 septembre 2011
par Pierre Latouche

Contact information

JPEG - 10.7 ko

Maître de Conférences (Associate Professor) in Applied Mathematics
Laboratoire SAMM, Université Paris 1 (Panthéon-Sorbonne)

Email : pierre.latouche@univ-paris1.fr
Address : Laboratoire SAMM, Université Paris 1
90 rue de Tolbiac, 75013 Paris, France
Phone : +33 (0)1 44 07 88 26 - Fax : +33 (0)1 44 07 89 25

Recent publications

News


Research interests :

_
- Network analysis
- Sparse inference
- High dimensional data
- Graphical models
- Model selection
- Bayesian analysis
- Variational approaches

Students :

_
- Marco Corneli (curent PhD student) 2014
- Pierre-Alexandre Mattei (curent PhD student) 2014
- Rawyia Zreik (curent PhD student) 2013
- Charles Abner-Dadi (ENS Cachan, MsC) 2013
- Ragheda el Hassan (ENS Cachan, MsC) 2013
- Yacine Jernite (ENS Cachan, MsC) 2012
- Laetitia Nouedoui (Paris 1, MsC) 2012
- Anne-Claire (ENSAE, Stage) 2009

Teaching :

_
- Probability and statistics
- Algebra, numerical analysis
- Datamining / Machine learning
- Programming

Some of my co-authors :

Christophe Ambroise, Etienne Birmelé, Charles Bouveyron, Julien Chiquet, Etienne Côme, Nial Friel, Stéphane Lamassé, Stéphane Robin, Fabrice Rossi, Jason Wyse

Softwares :

- Spinyreg (R package) : spare regression using spike and slab prior distributions
- Mixer (R package written in C++) : variational inference techniques for the stochastic bloc model. Can be used to classify the vertices of a network depending on their connection profiles
- Rambo (R package) : estimate the parameters, the number of classes and cluster vertices of a random network into groups with homogeneous connection profiles. The clustering is performed for directed graphs with typed edges (edges are assumed to be drawn from multinomial distributions) for which a partition of the vertices is available
- Netlab (Matlab) : some of the most important pattern recognition algorithms described by C.M. Bishop in “Neural Networks for Pattern Recognition” (Oxford University Press, 1995)
- Genoscript (WebObject) : a Web environment for transcriptom analysis


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