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)

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)