Uncertainty Wrappers for Data-Driven Models - Increase the Transparency of AI/ML-Based Models Through Enrichment with Dependable Situation-Aware Uncertainty Estimates. - Michael Kläs; Lena Sembach (SAFECOMP Workshops, 2019)

Riemannian Optimization for Variance Estimation in Linear Mixed Models. - Lena Sembach; Jan Pablo Burgard; Volker H. Schulz (CoRR, 2022)

A Riemannian Newton trust-region method for fitting Gaussian mixture models. - Lena Sembach; Jan Pablo Burgard; Volker Schulz 001 (Stat. Comput., 2022)