This paper puts forward a Bayesian unsmoothing method to model smoothing parameters probabilistically which mitigates limitations of traditional methods.
In an effort to close the gap between predictive performance and auditability in hybrid risk models the authors put forward an auditable hybrid quantile framework that anchors nonlinear gradient boosting corrections to a linear heterogeneous…
21 Sep 2026
21 Sep 2026
