Observational learning with position uncertainty. - Ignacio Monzón; Michael Rapp (J. Econ. Theory, 2014)

Detection of aromatic compounds in artificial gasoline with hybrid surface acoustic wave sensor array and a short packed column (SAW-GC). - Caroline Carriel Schmitt; Michael Rapp; Achim Voigt; Nicolaus Dahmen (IEEE SENSORS, 2016)

Long-Term Stability of Polymer-Coated Surface Transverse Wave Sensors for the Detection of Organic Solvent Vapors. - Ullrich Stahl; Achim Voigt; Marian Dirschka; Nicole Barié; Christiane Richter; Ansgar Waldbaur; Friederike J. Gruhl; Bastian E. Rapp; Michael Rapp; Kerstin Länge (Sensors, 2017)

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (PAKDD (1), 2018)

Learning Interpretable Rules for Multi-label Classification. - Eneldo Loza Mencía; Johannes Fürnkranz; Eyke Hüllermeier; Michael Rapp (CoRR, 2018)

Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning. - Yannik Klein; Michael Rapp; Eneldo Loza Mencía (DS, 2019)

On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (DS, 2019)

Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (CoRR, 2019)

Design and Simulation of a Wireless SAW-Pirani Sensor with Extended Range and Sensitivity. - Sofia Toto; Pascal Nicolay; Gian Luca Morini; Michael Rapp; Jan G. Korvink; Juergen J. Brandner (Sensors, 2019)

Correction: Design and Simulation of a Wireless SAW-Pirani Sensor with Extended Range and Sensitivity. - Sofia Toto; Pascal Nicolay; Gian Luca Morini; Michael Rapp; Jan G. Korvink; Juergen J. Brandner (Sensors, 2019)

On Aggregation in Ensembles of Multilabel Classifiers. - Vu-Linh Nguyen; Eyke Hüllermeier; Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (DS, 2020)

Learning Gradient Boosted Multi-label Classification Rules. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz; Vu-Linh Nguyen; Eyke Hüllermeier (ECML/PKDD (3), 2020)

Rule-Based Multi-label Classification: Challenges and Opportunities. - Eyke Hüllermeier; Johannes Fürnkranz; Eneldo Loza Mencía; Vu-Linh Nguyen; Michael Rapp (RuleML+RR, 2020)

Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning. - Johannes Fürnkranz; Eyke Hüllermeier; Eneldo Loza Mencía; Michael Rapp (CoRR, 2020)

Gradient-Based Label Binning in Multi-label Classification. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz; Eyke Hüllermeier (ECML/PKDD (3), 2021)

Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance. - Michael Rapp; Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (Frontiers Big Data, 2021)

BOOMER - An algorithm for learning gradient boosted multi-label classification rules. - Michael Rapp (Softw. Impacts, 2021)

A flexible class of dependence-aware multi-label loss functions. - Eyke Hüllermeier; Marcel Wever; Eneldo Loza Mencía; Johannes Fürnkranz; Michael Rapp (Mach. Learn., 2022)

Multi-label Rule Learning. - Michael Rapp (2022)

Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments. - Stefan Haas; Konstantin Hegestweiler; Michael Rapp; Maximilian Muschalik; Eyke Hüllermeier (Frontiers Artif. Intell., 2024)

On the efficient implementation of classification rule learning. - Michael Rapp; Johannes Fürnkranz; Eyke Hüllermeier (Adv. Data Anal. Classif., 2024)