Selected publications

• “Learning from both experts and data” with R. Besson and S. Allassonnière, Entropy (2019),
• “PAC-Bayesian aggregation of linear estimators” with L. Montuelle, Nonparametric Statistics (2019),
• “Adaptive Estimation in the Nonparametric Random Coefficients Binary Choice Model by Needlet Thresholding” with E. Gautier, EJS (2018),
• “Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach” with L. Montuelle, EJS (2014) (DOI:10.1214/14-EJS939)
• “Partition-Based Conditional Density Estimation” with S. Cohen, ESAIM P&S (2013) (DOI:10.1051/ps/2012017),
• “Radon needlet thresholding” with G. Kerkyacharian and D. Picard, Bernoulli (2012) (DOI:10.3150/10-BEJ340),
• “Bandlet Image Estimation with Model Selection” with Ch. Dossal and S. Mallat, Signal Processing (2011) (DOI:10.1016/j.sigpro.2011.01.013),
• “Adaptive Dantizg density estimation” with K. Bertin and V. Rivoirard, Annales de l’IHP, Probability and Statistics (2011) (DOI:10.1214/09-AIHP351),
• “Inversion of noisy Radon transform by SVD based needlets” with G. Kerkyacharian, G. Kyriasis, P. Petrushev and D. Picard,ACHA (2010) (DOI:10.1016/j.acha.2009.06.001),
• “Thresholding methods to estimate the copula density” with F. Autin and K. Tribouley, JMVA (2010) (DOI:10.1016/j.jmva.2009.07.009),
• “Maxisets for Model Selection” with F. Autin, J.-M. Loubes and V. Rivoirard, Constructive Approximation (2010) (DOI:10.1007/s00365-009-9062-2),
• “Sparse Geometrical Image Approximation with Bandelets” with S. Mallat, IEEE Transaction on Image Processing (2005) (DOI:10.1109/TIP.2005.843753),
• “Bandelet Image Approximation and Compression” with S. Mallat, SIAM MMS (2005) (DOI:10.1137/040619454).

Last Preprints

• “A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task” with R. Besson, S. Allassonnière, J. Stirnemann, E. Spaggiari and A. Neuraz,
• “Clustering and Model Selection via Penalized Likelihood for Different-sized Categorical Data Vectors” with E. Dorman,
• “Conditional Density Estimation by Penalized Likelihood Model Selection and Applications” with S. Cohen.

For more details, see the research page or the comprehensive list of publications

Current students

• Frédéric Logé-Munérel, PhD, 2017-, CIFRE Air Liquide, Planning and Reinforcement Learning
• Angie Pineda, Post Doc, 2018-, C’IL-LICO project, Health data
• Thomas Galtier, Post Doc, 2019-, HealthChain project, Data Valuation, Federated Learning
• Paul Monchot, PhD, 2020-, CIFRE LNE, Supervised learning and sensibility
• Fleur Gaudfernau, PhD with S. Allassonière, 2020-, Diagnosis in IRM

Former students

• Rémi Besson, PhD with S. Allassonière, 2016-2019, Rare Disease Diagnosis Optimization – now Post Doc at Université de Paris
• Marco Brigham, Post Doc, 2017-2019, Morpheo project, EEG Analysis – now CSO at Moonoia
• Esther Derman, PhD, 2016-2017, Model Based Histogram Clustering – moved to Israel, now PhD student in the Technion
• Solenne Thivin, PhD, 2012-2015, CIFRE Thales Optronics, Detection on Complex Textures – now professor in high school
• Lucie Montuelle, PhD, 2011-2014, Conditional Density Estimation – now Data Scientist at RTE
• Joseph Salmon, PhD, 2007-2010, Estimator Aggregation – now full professor at Université de Montpellier