Tempus Volat, Hora Fugit - A Survey of Dynamic Network Models in Discrete and Continuous Time. - Cornelius Fritz; Michael Lebacher; Göran Kauermann (CoRR, 2019)

The Thousand Faces of Explainable AI Along the Machine Learning Life Cycle: Industrial Reality and Current State of Research. - Thomas Decker 004; Ralf Gross; Alexander Koebler; Michael Lebacher; Ronald Schnitzer; Stefan H. Weber (HCI (40), 2023)

Does Your Model Think Like an Engineer? Explainable AI for Bearing Fault Detection with Deep Learning. - Thomas Decker 004; Michael Lebacher; Volker Tresp (ICASSP, 2023)

Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts. - Thomas Decker 004; Michael Lebacher; Volker Tresp (INDIN, 2023)

Towards Scenario-Based Safety Validation for Autonomous Trains with Deep Generative Models. - Thomas Decker 004; Ananta R. Bhattarai; Michael Lebacher (SAFECOMP, 2023)

Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. - Thomas Decker 004; Alexander Koebler; Michael Lebacher; Ingo Thon; Volker Tresp; Florian Buettner 001 (KDD, 2024)