An inverse parameter identification procedure assessing the quality of the estimates using Bayesian neural networks. - Jörg F. Unger; Carsten Könke (Appl. Soft Comput., 2011)

Efficient structural reliability analysis by using a PGD model in an adaptive importance sampling schema. - Annika Robens-Radermacher; Jörg F. Unger (Adv. Model. Simul. Eng. Sci., 2020)

Multiscale modeling of linear elastic heterogeneous structures based on a localized model order reduction approach. - Philipp Diercks; Karen Veroy; Annika Robens-Radermacher; Jörg F. Unger (CoRR, 2022)

Evaluation of tools for describing, reproducing and reusing scientific workflows. - Philipp Diercks; Dennis Gläser; Ontje Lünsdorf; Michael Selzer; Bernd Flemisch; Jörg F. Unger (CoRR, 2022)

Model bias identification for Bayesian calibration of stochastic digital twins of bridges. - Daniel Andrés Arcones; Martin Weiser; Phaedon-Stelios Koutsourelakis; Jörg F. Unger (CoRR, 2023)

Adaptive Gaussian Process Regression for Bayesian inverse problems. - Paolo Villani; Jörg F. Unger; Martin Weiser (CoRR, 2024)

Embedded Model Bias Quantification with Measurement Noise for Bayesian Model Calibration. - Daniel Andrés Arcones; Martin Weiser; Phaedon-Stelios Koutsourelakis; Jörg F. Unger (CoRR, 2024)

Posterior sampling with Adaptive Gaussian Processes in Bayesian parameter identification. - Paolo Villani; Daniel Andrés Arcones; Jörg F. Unger; Martin Weiser (CoRR, 2024)

Integrating custom constitutive models into FEniCSx: A versatile approach and case studies. - Sjard Mathis Rosenbusch; Philipp Diercks; Vitaliy Kindrachuk; Jörg F. Unger (Adv. Eng. Softw., 2025)