Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage. - Elena Erdmann; Karin Boczek; Lars Koppers; Gerret von Nordheim; Christian Pölitz; Alejandro Molina 001; Katharina Morik; Henrik Müller; Jörg Rahnenführer; Kristian Kersting (CoRR, 2016)

Towards Automated Sign Language Production: A Pipeline for Creating Inclusive Virtual Humans. - Lucas Bernhard; Fabrizio Nunnari; Amelie Unger; Judith Bauerdiek; Christian Dold; Marcel Hauck; Alexander Stricker; Tobias Baur 001; Alexander Heimerl; Elisabeth André; Melissa Reinecker; Cristina España-Bonet; et al. (PETRA, 2022)

Knowledge Graph Injection for Reinforcement Learning. - Robert Wardenga; Liubov Kovriguina; Dmitrii Pliukhin; Daniil Radyush; Ivan SmoliakoV; Yuan Xue; Henrik Müller; Aleksei Pismerov; Dmitry Mouromtsev; Daniel Kudenko (DL4KG@ISWC, 2023)

Debunking Disinformation with GADMO: A Topic Modeling Analysis of a Comprehensive Corpus of German-language Fact-Checks. - Jonas Rieger; Nico Hornig; Jonathan Flossdorf; Henrik Müller; Stephan Mündges; Carsten Jentsch; Jörg Rahnenführer; Christina Elmer (LDK, 2023)

Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders. - Jurek Leonhardt; Henrik Müller; Koustav Rudra; Megha Khosla; Abhijit Anand; Avishek Anand (ACM Trans. Inf. Syst., 2024)

Improving the Effectiveness of Potential-based Reward Shaping in Reinforcement Learning. - Henrik Müller; Daniel Kudenko (AAMAS, 2025)

Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models. - Kai-Robin Lange; Tobias Schmidt; Matthias Reccius; Henrik Müller; Michael Roos; Carsten Jentsch (Text2Story@ECIR, 2025)

Identifying economic narratives in large text corpora - An integrated approach using Large Language Models. - Tobias Schmidt; Kai-Robin Lange; Matthias Reccius; Henrik Müller; Michael Roos; Carsten Jentsch (CoRR, 2025)

Using incomplete and incorrect plans to shape reinforcement learning in long-sequence sparse-reward tasks. - Henrik Müller; Lukas Berg; Daniel Kudenko (Neural Comput. Appl., 2025)