UBY - A Large-Scale Unified Lexical-Semantic Resource Based on LMF. - Iryna Gurevych; Judith Eckle-Kohler; Silvana Hartmann; Michael Matuschek; Christian M. Meyer; Christian Wirth 001 (EACL, 2012)

EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning. - Christian Wirth 001; Johannes Fürnkranz (ACML, 2013)

A Policy Iteration Algorithm for Learning from Preference-Based Feedback. - Christian Wirth 001; Johannes Fürnkranz (IDA, 2013)

Preference Learning from Annotated Game Databases. - Christian Wirth 001; Johannes Fürnkranz (LWA, 2014)

On Learning From Game Annotations. - Christian Wirth 001; Johannes Fürnkranz (IEEE Trans. Comput. Intell. AI Games, 2015)

Model-Free Preference-Based Reinforcement Learning. - Christian Wirth 001; Johannes Fürnkranz; Gerhard Neumann (AAAI, 2016)

A Survey of Preference-Based Reinforcement Learning Methods. - Christian Wirth 001; Riad Akrour; Gerhard Neumann; Johannes Fürnkranz (J. Mach. Learn. Res., 2017)

Efficient Preference-based Reinforcement Learning - Christian Wirth 001 (2017)

Preference-Based Monte Carlo Tree Search. - Tobias Joppen; Christian Wirth 001; Johannes Fürnkranz (KI, 2018)

Informed Hybrid Game Tree Search for General Video Game Playing. - Tobias Joppen; Miriam Ulrike Moneke; Nils Schröder; Christian Wirth 001; Johannes Fürnkranz (IEEE Trans. Games, 2018)

Concept Embeddings for Fuzzy Logic Verification of Deep Neural Networks in Perception Tasks. - Gesina Schwalbe; Christian Wirth 001; Ute Schmid (CoRR, 2022)

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey. - Julian Wörmann; Daniel Bogdoll; Etienne Bührle; Han Chen; Evaristus Fuh Chuo; Kostadin Cvejoski; Ludger van Elst; Tobias Gleißner; Philip Gottschall; Stefan Griesche; Christian Hellert; Christian Hesels; et al. (CoRR, 2022)

Efficient Utility Function Learning for Multi-Objective Parameter Optimization with Prior Knowledge. - Farha A. Khan; Jörg P. Dietrich; Christian Wirth 001 (CoRR, 2022)

Post-hoc Rule Based Explanations for Black Box Bayesian Optimization. - Tanmay Chakraborty; Christian Wirth 001; Christin Seifert (ECAI Workshops (1), 2023)

Overcoming the Limitations of Localization Uncertainty: Efficient and Exact Non-linear Post-processing and Calibration. - Moussa Kassem Sbeyti; Michelle Karg; Christian Wirth 001; Azarm Nowzad; Sahin Albayrak (ECML/PKDD (5), 2023)

Informed Priors for Knowledge Integration in Trajectory Prediction. - Christian Schlauch; Christian Wirth 001; Nadja Klein (ECML/PKDD (5), 2023)

Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration. - Moussa Kassem Sbeyti; Michelle Karg; Christian Wirth 001; Azarm Nowzad; Sahin Albayrak (CoRR, 2023)

Informed Spectral Normalized Gaussian Processes for Trajectory Prediction. - Christian Schlauch; Christian Wirth 001; Nadja Klein (ECAI, 2024)

Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. - Moussa Kassem Sbeyti; Michelle Karg; Christian Wirth 001; Nadja Klein; Sahin Albayrak (UAI, 2024)

Explainable Bayesian Optimization. - Tanmay Chakraborty; Christin Seifert; Christian Wirth 001 (CoRR, 2024)

Comparative Explanations: Explanation Guided Decision Making for Human-in-the-Loop Preference Selection. - Tanmay Chakraborty; Christian Wirth 001; Christin Seifert (CoRR, 2025)

Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification. - Kumar Manas; Christian Schlauch; Adrian Paschke; Christian Wirth 001; Nadja Klein (CoRR, 2025)

Explanation format does not matter; but explanations do - An Eggsbert study on explaining Bayesian Optimisation tasks. - Tanmay Chakraborty; Marion Koelle; Jörg Schlötterer; Nadine Schlicker; Christian Wirth 001; Christin Seifert (CoRR, 2025)

Generative AI for Autonomous Driving: A Review. - Katharina Winter; Abhishek Vivekanandan; Rupert Polley; Yinzhe Shen; Christian Schlauch; Mohamed-Khalil Bouzidi; Bojan Derajic; Natalie Grabowsky; Annajoyce Mariani; Dennis Rochau; Giovanni Lucente; Harsh Yadav; et al. (CoRR, 2025)