Efficient Decentralized Deep Learning by Dynamic Model Averaging. - Michael Kamp; Linara Adilova; Joachim Sicking; Fabian Hüger; Peter Schlicht; Tim Wirtz; Stefan Wrobel (ECML/PKDD (1), 2018)

Street-Map Based Validation of Semantic Segmentation in Autonomous Driving. - Laura von Rüden; Tim Wirtz; Fabian Hüger; Jan David Schneider; Nico Piatkowski; Christian Bauckhage (ICPR, 2020)

Characteristics of Monte Carlo Dropout in Wide Neural Networks. - Joachim Sicking; Maram Akila; Tim Wirtz; Sebastian Houben; Asja Fischer (CoRR, 2020)

Towards Map-Based Validation of Semantic Segmentation Masks. - Laura von Rüden; Tim Wirtz; Fabian Hüger; Jan David Schneider; Christian Bauckhage (CoRR, 2020)

Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. - Joachim Sicking; Maram Akila; Maximilian Pintz; Tim Wirtz; Asja Fischer; Stefan Wrobel (CoRR, 2020)

Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation. - Linara Adilova; Elena Schulz; Maram Akila; Sebastian Houben; Jan David Schneider; Fabian Hüger; Tim Wirtz (CVPR Workshops, 2021)

Supporting verification of news articles with automated search for semantically similar articles. - Vishwani Gupta; Katharina Beckh; Sven Giesselbach; Dennis Wegener; Tim Wirtz (ROMCIR@ECIR, 2021)

Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. - Julia Rosenzweig; Eduardo Brito; Hans-Ulrich Kobialka; Maram Akila; Nico M. Schmidt; Peter Schlicht; Jan David Schneider; Fabian Hüger; Matthias Rottmann; Sebastian Houben; Tim Wirtz (IV Workshops, 2021)

A Novel Regression Loss for Non-Parametric Uncertainty Optimization. - Joachim Sicking; Maram Akila; Maximilian Pintz; Tim Wirtz; Asja Fischer; Stefan Wrobel (CoRR, 2021)

Approaching Neural Network Uncertainty Realism. - Joachim Sicking; Alexander Kister; Matthias Fahrland; Stefan Eickeler; Fabian Hüger; Stefan Rüping 001; Peter Schlicht; Tim Wirtz (CoRR, 2021)

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. - Sebastian Houben; Stephanie Abrecht; Maram Akila; Andreas Bär; Felix Brockherde; Patrick Feifel; Tim Fingscheidt; Sujan Sai Gannamaneni; Seyed Eghbal Ghobadi; Ahmed Hammam; Anselm Haselhoff; Felix Hauser; et al. (CoRR, 2021)

DenseHMM: Learning Hidden Markov Models by Learning Dense Representations. - Joachim Sicking; Maximilian Pintz; Maram Akila; Tim Wirtz (ICPRAM, 2022)

Tailored Uncertainty Estimation for Deep Learning Systems. - Joachim Sicking; Maram Akila; Jan David Schneider; Fabian Hüger; Peter Schlicht; Tim Wirtz; Stefan Wrobel (CoRR, 2022)

Multi-Agent Neural Rewriter for Vehicle Routing with Limited Disclosure of Costs. - Nathalie Paul; Tim Wirtz; Stefan Wrobel; Alexander Kister (CoRR, 2022)

Reinforcement Learning for Segmented Manufacturing. - Nathalie Paul; Alexander Kister; Thorben Schnellhardt; Maximilian Fetz; Dirk Hecker; Tim Wirtz (PKDD/ECML Workshops (4), 2023)

Big Data 2.0 - mit synthetischen Daten KI-Systeme stärken. - Dirk Hecker; Angi Voss; Gerhard Paaß; Tim Wirtz (Wirtschaftsinformatik Manag., 2023)

Wasserstein dropout. - Joachim Sicking; Maram Akila; Maximilian Pintz; Tim Wirtz; Stefan Wrobel; Asja Fischer (Mach. Learn., 2024)

Reinforcement Learning for Efficient Returns Management. - Pascal Linden; Nathalie Paul; Tim Wirtz; Stefan Wrobel (CoRR, 2025)