A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making. - Max Schemmer; Patrick Hemmer; Maximilian Nitsche; Niklas Kühl 001; Michael Vössing (AIES, 2022)

Anomaly Detection in Autonomous Driving: A Survey. - Daniel Bogdoll; Maximilian Nitsche; J. Marius Zöllner (CVPR Workshops, 2022)

Multimodal Detection of Unknown Objects on Roads for Autonomous Driving. - Daniel Bogdoll; Enrico Eisen; Maximilian Nitsche; Christin Scheib; J. Marius Zöllner (SMC, 2022)

Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers. - Daniel Bogdoll; Meng Zhang; Maximilian Nitsche; J. Marius Zöllner (CoRR, 2022)

AB2CD: AI for Building Climate Damage Classification and Detection. - Maximilian Nitsche; S. Karthik Mukkavilli; Niklas Kühl 001; Thomas Brunschwiler (CoRR, 2023)

Investigating the Role of Explainability and AI Literacy in User Compliance. - Niklas Kühl 001; Christian Meske; Maximilian Nitsche; Jodie Lobana (CoRR, 2024)

Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation. - Clive Tinashe Marimo; Benedikt Blumenstiel; Maximilian Nitsche; Johannes Jakubik; Thomas Brunschwiler (CoRR, 2025)