Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition. - Jeffrey Näf; Marc S. Paolella; Pawel Polak (J. Multivar. Anal., 2019)

The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis. - Patrick Bachmann; Markus Meierer; Jeffrey Näf (Mark. Sci., 2021)

On the use of random forest for two-sample testing. - Simon Hediger; Loris Michel; Jeffrey Näf (Comput. Stat. Data Anal., 2022)

Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression. - Domagoj Cevid; Loris Michel; Jeffrey Näf; Peter Bühlmann; Nicolai Meinshausen (J. Mach. Learn. Res., 2022)

Confidence and Uncertainty Assessment for Distributional Random Forests. - Jeffrey Näf; Corinne Emmenegger; Peter Bühlmann; Nicolai Meinshausen (J. Mach. Learn. Res., 2023)

R-NL: Covariance Matrix Estimation for Elliptical Distributions Based on Nonlinear Shrinkage. - Simon Hediger; Jeffrey Näf; Michael Wolf (IEEE Trans. Signal Process., 2023)

MMD-based Variable Importance for Distributional Random Forest. - Clément Bénard; Jeffrey Näf; Julie Josse (AISTATS, 2024)