Publications :

• Salhi, S. et al. (2025) ‘’ Clinical Evaluation of an Automated Pan-Organ Combined PD-L1 Scoring Using Artificial Intelligence on Immunostained Whole Slide Images’’. ESMO Real World Data and Digital Oncology.

• Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’Disentangled Deep Smoothed Bootstrap for Fair Imbalanced Regression’’. KES2025.

• Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’KurtHGR: A Neural Maximal Correlation for Tabular Datasets’’. KES2025.

• Stocksieker, S., Pommeret, D. (2025) ““SHGR: A generalized Maximal Correlation Coefficient”. Neurips 2025.

• Thomas, F., Pommeret, D., Guinaudeau, E., Poulet, B., Salhi, Y., Chetritt, J. (2025) “Coping with inter-observer variability when assessing AI for scoring of HER2-stained whole slides”. Journal Clinical of Oncology.

• Stocksieker, S., Pommeret, D., Charpentier, A. (2024) “Generalized Smoothed Bootstrap for Imbalanced Regression” CIKM 2024

• Stocksieker, S., Pommeret, D., Charpentier, A. (2024) “Data Augmentation with Variational Autoencoder for Imbalanced Dataset” ICONIP 2024

• Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2024) “Contamination-source based K-sample clustering” Journal of Machine Learning Research

• Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Generalized Oversampling for Learning from Imbalanced Dataset and Associated Theory: Application in Regression" Transactions on Machine Learning research. 

• Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Boarding for ISS: Imbalanced Self-Supervised Discovery of a Scaled Autoencoder for Mixed Tabular Datasets" IEEE WCCI. 

• Mnatsakanov, R., Pommeret, D. (2024) " On recovering the relative distribution. Part 1: The moment-recovered approach" Statistics & Probability Letters.

• Ngounou-Bakam, Y., Pommeret, D. (2024) "Smooth test for equality of copulas" Electronic Journal of Statistics.

• Ngounou-Bakam, Y., Pommeret, D. (2023) "Nonparametric estimation of copulas and copula densities by orthogonal projections" Econometrics and Statistics.

• Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2023) "Two sample contamination model test" Bernoulli. 

• Stocksieker, S., Pommeret, D., Charpentier, A. (2023)  "Data Augmentation for Imbalanced Regression" AISTATS.

• Ngounou-Bakam, Y., Pommeret, D. (2022) "Kcop: Smooth Test for Equality of Copulas and Clustering Multivariate" R Package.

• Fuchs, R., Thyssen, M., Creach, V., Dugenne, M., Izard, L., Latimier, M., Louchart, A., Marrec, P.,  Rijkeboer, M., Grégori, G., Pommeret, D. (2022) "Automatic recognition of flow cytometric phytoplankton functional groups using convolutional neural networks". Limnology and Oceanography Methods. 

• Fuchs, R., Pommeret, D., Stocksieker, S. (2022) "MIAMI: MIxed data Augmentation MIxture". ICCSA Proceedings – Lecture Notes in Computer Science.

• Fuchs, R., Pommeret, D., Stocksieker, S. (2022) "MI2AMI: Missing data imputation using Mixed Deep Gaussian Mixture Models". LOD Proceedings – Lecture Notes in Computer Science.

• Pommeret, D., Reboul, L., Yao, A.F. (2022) "Testing the equality of the  laws of two strictly stationary processes". Statistical Inference for Stochastic Processes.  

• Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2022) “Semiparametric two-sample admixture components comparison test: The symmetric case”. Journal of Statistical Planning and Inference.

• Fuchs, R., Pommeret, D., Viroli, C. (2021) “Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets”. Advances in Data Analysis and Classification.

• Soubeyrand, S., Ribaud, M., Baudrot, V., Allard, D., Pommeret. D, Roques, L. (2020) “COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)” PLOS ONE.

• Pommeret, D., Vandekerkhove, P. (2019) “ Semiparametric density testing in the contamination model”. Electronic Journal of Statistics.

• Doukhan, P., Grublit, I., Pommeret, D., Reboul, L. (2019) “Comparing the marginal densities of two strictly stationary linear processes”. Annals of the Institute of Statistical Mathematics.

• Pommeret, D., Reboul, L. (2018) “Approximating the Probability Density Function of a Transformation of Random Variables”. Methodology and Computing in Applied Probability.

• Doukhan, P., Joseph Rynkiewicz, J., Pommeret, D., Salhi, Y. (2017) “A Class of Random Field Memory Models for Mortality Forecasting”. Insurance Mathematics and Economics

• Goffard, P.O., Loisel, S., Pommeret, D. (2017) “Polynomial approximation for bivariate aggregate claims amount probability distributions”. Methodology and Computing in Applied Probability.

• Boutahar, M., Pommeret, D. (2016) “A test for the equality of transformations of two random variables”. ESAIM P&S.

• Goffard, P.O., Loisel, S., Pommeret, D. (2016) “A polynomial expansion to approximate the ultimate ruin probability in the coumpound Poisson ruin model”. Journal of Computational and Applied Mathematics.

• Doukhan, P., Pommeret, D., Reboul, L. (2015) “Data Driven Smooth Test of Comparison of Dependent Sequences”. Journal of Multivariate Analysis.

• Pommeret, D. (2015) “Comparing two mixing densities in nonparametric mixtures”. Sankhya

• Pommeret, D. (2013) “A two-sample test when data are contaminated”. Statistical Methods and Applications.

• Boutahar, M. Ghattas, B., Pommeret, D. (2013) “Nonparametric comparison of several transformations of distribution functions”. Journal of Nonparametric Statistics.

• Baragatti, M., Grimaud, A., Pommeret, D. (2013) “Parallel tempering with Equi-Energy moves”. Statistics and Computing.

• Baragatti, A. Grimaud, A., Pommeret, D. (2012) “Likelihood-free parallel tempering”. Statistics and Computing.

• Druilhet, P., Pommeret, D. (2012) “Invariant conjugate analysis for exponential families”. Bayesian Analysis.

• Baragatti, M., Pommeret, D. (2011) “A study of variable selection using g-prior distribution with ridge parameter”. Computational Statistics and Data Analysis.

• Guyon, E., Pommeret, D. (2011) “Imputation by PLS regression for linear mixed models”. Journal de la Société Francaise de Statistique.

• Pommeret, D. (2011) “Data driven smooth test for contaminated data”. Journal of Statistical Theory and Practice.

• Ghattas, B., Pommeret, D., Reboul, L., Yao, A.F. (2011) “Data driven smooth test for paired populations”. Journal of Statistical Planning and Inference.

• Baragatti, M., Pommeret, D. (2011) Comments on “Bayesian variable selection for disease classification using gene expression data”. Bioinformatics.

• Pommeret (2010) “Testing Mixed Distributions when the Mixing Distribution Is Known”. Advances in Data Analysis, Data Handling and Business Intelligence. Studies in Classification,Data Analysis, and Knowledge Organization.

Arxiv & Hal : 

• Stocksieker, S., Pommeret, D., Charpentier, A. "Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory"

• Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. "Contamination-source based K-sample clustering"