Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness. - Mohammadreza Amirian; Lukas Tuggener; Ricardo Chavarriaga; Yvan Putra Satyawan; Frank-Peter Schilling; Friedhelm Schwenker; Thilo Stadelmann (TAILOR, 2020)

A Survey of Un-, Weakly-, and Semi-Supervised Learning Methods for Noisy, Missing and Partial Labels in Industrial Vision Applications. - Niclas Simmler; Pascal Sager; Philipp Andermatt; Ricardo Chavarriaga; Frank-Peter Schilling; Matthias Rosenthal; Thilo Stadelmann (SDS, 2021)

AI Assessment in Practice: Implementing a Certification Scheme for AI Trustworthiness (Academic Track). - Carmen Frischknecht-Gruber; Philipp Denzel; Monika Reif; Yann Billeter; Stefan Brunner; Oliver Forster; Frank-Peter Schilling; Joanna Weng; Ricardo Chavarriaga (SAIA, 2024)

MLOps as Enabler of Trustworthy AI. - Yann Billeter; Philipp Denzel; Ricardo Chavarriaga; Oliver Forster; Frank-Peter Schilling; Stefan Brunner; Carmen Frischknecht-Gruber; Monika Reif; Joanna Weng (SDS, 2024)

Towards the Certification of AI-based Systems. - Philipp Denzel; Stefan Brunner; Yann Billeter; Oliver Forster; Carmen Frischknecht-Gruber; Monika Reif; Frank-Peter Schilling; Joanna Weng; Ricardo Chavarriaga; Amin Amini 003; Marco Repetto; Arman Iranfar (SDS, 2024)

Artifact Reduction in 3D and 4D Cone-Beam Computed Tomography Images With Deep Learning: A Review. - Mohammadreza Amirian; Daniel Barco; Ivo Herzig; Frank-Peter Schilling (IEEE Access, 2024)

MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomography. - Daniel Barco; Marc Stadelmann; Martin Oswald; Ivo Herzig; Lukas Lichtensteiger; Pascal Paysan; Igor Peterlík; Michal Walczak; Bjoern Menze; Frank-Peter Schilling (CoRR, 2025)