LocalGLMnet: interpretable deep learning for tabular data. - Ronald Richman; Mario V. Wüthrich (CoRR, 2021)

A multi-task network approach for calculating discrimination-free insurance prices. - Mathias Lindholm; Ronald Richman; Andreas Tsanakas; Mario V. Wüthrich (CoRR, 2022)

A Discussion of Discrimination and Fairness in Insurance Pricing. - Mathias Lindholm; Ronald Richman; Andreas Tsanakas; Mario V. Wüthrich (CoRR, 2022)

Interpreting deep learning models with marginal attribution by conditioning on quantiles. - Michael Merz; Ronald Richman; Andreas Tsanakas; Mario V. Wüthrich (Data Min. Knowl. Discov., 2022)

Smoothness and monotonicity constraints for neural networks using ICEnet. - Ronald Richman; Mario V. Wüthrich (CoRR, 2023)

Conditional expectation network for SHAP. - Ronald Richman; Mario V. Wüthrich (CoRR, 2023)

LASSO regularization within the LocalGLMnet architecture. - Ronald Richman; Mario V. Wüthrich (Adv. Data Anal. Classif., 2023)

Multiple Yield Curve Modeling and Forecasting using Deep Learning. - Ronald Richman; Salvatore Scognamiglio (CoRR, 2024)

The Credibility Transformer. - Ronald Richman; Salvatore Scognamiglio; Mario V. Wüthrich (CoRR, 2024)