Orthogonal and pseudo-orthogonal multi-dimensional Appell polynomials. - Denys Pommeret (Appl. Math. Comput., 2001)

Testing Mixed Distributions when the Mixing Distribution Is Known. - Denys Pommeret (GfKl, 2008)

Comments on 'Bayesian variable selection for disease classification using gene expression data'. - Meïli C. Baragatti; Denys Pommeret (Bioinform., 2011)

A study of variable selection using g-prior distribution with ridge parameter. - Meïli C. Baragatti; Denys Pommeret (Comput. Stat. Data Anal., 2012)

Parallel tempering with equi-energy moves. - Meïli C. Baragatti; Agnès Grimaud; Denys Pommeret (Stat. Comput., 2013)

Likelihood-free parallel tempering. - Meïli C. Baragatti; Agnès Grimaud; Denys Pommeret (Stat. Comput., 2013)

A two-sample test when data are contaminated. - Denys Pommeret (Stat. Methods Appl., 2013)

Data driven smooth test of comparison for dependent sequences. - Paul Doukhan; Denys Pommeret; Laurence Reboul (J. Multivar. Anal., 2015)

A polynomial expansion to approximate the ultimate ruin probability in the compound Poisson ruin model. - Pierre-Olivier Goffard; Stéphane Loisel; Denys Pommeret (J. Comput. Appl. Math., 2016)

Mixed data Deep Gaussian Mixture Model: A clustering model for mixed datasets. - Robin Fuchs; Denys Pommeret; Cinzia Viroli (CoRR, 2020)

MIAMI: MIxed Data Augmentation MIxture. - Robin Fuchs; Denys Pommeret; Samuel Stocksieker (ICCSA (1), 2022)

MI2AMI: Missing Data Imputation Using Mixed Deep Gaussian Mixture Models. - Robin Fuchs; Denys Pommeret; Samuel Stocksieker (LOD (1), 2022)

Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets. - Robin Fuchs; Denys Pommeret; Cinzia Viroli (Adv. Data Anal. Classif., 2022)

Data Augmentation for Imbalanced Regression. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (AISTATS, 2023)

Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (CoRR, 2023)

Data Augmentation with Variational Autoencoder for Imbalanced Dataset. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (ICONIP (2), 2024)

Boarding for ISS: Imbalanced Self-Supervised Discovery of a Scaled Autoencoder for Mixed Tabular Datasets. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (IJCNN, 2024)

Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory: Application in Regression. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (Trans. Mach. Learn. Res., 2024)

Disentangled Deep Smoothed Bootstrap for Fair Imbalanced Regression. - Samuel Stocksieker; Denys Pommeret; Arthur Charpentier (CoRR, 2025)