André Artelt

Adversarial Attacks Hidden in Plain Sight

2020 · Lecture notes in computer science

Convolutional neural networks have been used to achieve a string of successes during recent years, but their lack of interpretability remains a serious issue. Adversarial examples are designed to deliberately fool neural networks into making …

Localization of Concept Drift: Identifying the Drifting Datapoints

2022 · 2022 International Joint Conference on Neural Networks (IJCNN)

The notion of concept drift refers to the phenomenon that the distribution which is underlying the observed data changes over time. As a consequence machine learning models may become inaccurate and need adjustment. While there …

On the Hardness of Computing Counterfactual and Semifactual Explanations in XAI

2026

Providing clear explanations to the choices of machine learning models is essential for these models to be deployed in crucial applications. Counterfactual and semi-factual explanations have emerged as two mechanisms for providing users with insights …