Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm. - Robin Senge; Eyke Hüllermeier (LWA, 2009)

Pattern trees for regression and fuzzy systems modeling. - Robin Senge; Eyke Hüllermeier (FUZZ-IEEE, 2010)

Top-Down Induction of Fuzzy Pattern Trees. - Robin Senge; Eyke Hüllermeier (IEEE Trans. Fuzzy Syst., 2011)

On the Problem of Error Propagation in Classifier Chains for Multi-label Classification. - Robin Senge; Juan José del Coz; Eyke Hüllermeier (GfKl, 2012)

Fuzzy Pattern Trees: Ein alternativer Ansatz zur Fuzzy-Modellierung. - Robin Senge; Thomas Fober; Maryam Nasiri; Eyke Hüllermeier (Autom., 2012)

Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures. - Eyke Hüllermeier; Maria Rifqi; Sascha Henzgen; Robin Senge (IEEE Trans. Fuzzy Syst., 2012)

Fuzzy pattern trees as an alternative to rule-based fuzzy systems: Knowledge-driven, data-driven and hybrid modeling of color yield in polyester dyeing. - Maryam Nasiri; Thomas Fober; Robin Senge; Eyke Hüllermeier (IFSA/NAFIPS, 2013)

Rectifying Classifier Chains for Multi-Label Classification. - Robin Senge; Juan José del Coz; Eyke Hüllermeier (LWA, 2013)

Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction. - Dominik Heider; Robin Senge; Weiwei Cheng; Eyke Hüllermeier (Bioinform., 2013)

Evolving fuzzy pattern trees for binary classification on data streams. - Ammar Shaker; Robin Senge; Eyke Hüllermeier (Inf. Sci., 2013)

Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. - Robin Senge; Stefan Bösner; Krzysztof Dembczynski; Jörg Haasenritter; Oliver Hirsch; Norbert Donner-Banzhoff; Eyke Hüllermeier (Inf. Sci., 2014)

Dependent binary relevance models for multi-label classification. - Elena Montañés; Robin Senge; José Barranquero; José Ramón Quevedo; Juan José del Coz; Eyke Hüllermeier (Pattern Recognit., 2014)

Machine learning methods for fuzzy pattern tree induction. - Robin Senge (2014)

Fast Fuzzy Pattern Tree Learning for Classification. - Robin Senge; Eyke Hüllermeier (IEEE Trans. Fuzzy Syst., 2015)

Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. - Mona Riemenschneider; Robin Senge; Ursula Neumann; Eyke Hüllermeier; Dominik Heider (BioData Min., 2016)

Demand Forecasting using Long Short-Term Memory Neural Networks. - Marta Golabek; Robin Senge; Rainer Neumann (CoRR, 2020)

Distributional regression for demand forecasting in e-grocery. - Matthias Ulrich; Hermann Jahnke; Roland Langrock; Robert Pesch; Robin Senge (Eur. J. Oper. Res., 2021)

Teacher Network Calibration Improves Cross-Quality Knowledge Distillation. - Pia Cuk; Robin Senge; Mikko Lauri; Simone Frintrop (CoRR, 2023)