Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers. - Georg Siedel; Silvia Vock; Andrey Morozov 001; Stefan Voß 002 (AISafety@IJCAI, 2022)

Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions. - Georg Siedel; Silvia Vock; Andrey Morozov 001 (CoRR, 2023)

Investigating the Corruption Robustness of Image Classifiers with Random p-norm Corruptions. - Georg Siedel; Weijia Shao; Silvia Vock; Andrey Morozov 001 (VISIGRAPP (2): VISAPP, 2024)

A practical approach to evaluating the adversarial distance for machine learning classifiers. - Georg Siedel; Ekagra Gupta; Andrey Morozov 001 (CoRR, 2024)

Combined Image Data Augmentations diminish the benefits of Adaptive Label Smoothing. - Georg Siedel; Ekagra Gupta; Weijia Shao; Silvia Vock; Andrey Morozov 001 (CoRR, 2025)