Jeffrey Näf

According to our database, Jeffrey Näf authored at least 7 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

MMD-based Variable Importance for Distributional Random Forest.

Clément Bénard, Jeffrey Näf, Julie Josse

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

R-NL: Covariance Matrix Estimation for Elliptical Distributions Based on Nonlinear Shrinkage.

Simon Hediger, Jeffrey Näf, Michael Wolf

IEEE Trans. Signal Process., 2023

Confidence and Uncertainty Assessment for Distributional Random Forests.

Jeffrey Näf, Corinne Emmenegger, Peter Bühlmann, Nicolai Meinshausen

J. Mach. Learn. Res., 2023

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

On the use of random forest for two-sample testing.

Simon Hediger, Loris Michel, Jeffrey Näf

Comput. Stat. Data Anal., 2022

2021

The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis.

Patrick Bachmann, Markus Meierer, Jeffrey Näf

Mark. Sci., 2021

2019

Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition.

Jeffrey Näf, Marc S. Paolella, Pawel Polak

J. Multivar. Anal., 2019