Dynamic Classifier Chain with Random Decision Trees. - Moritz Kulessa; Eneldo Loza Mencía (DS, 2018)

Model-based Approximate Query Processing. - Moritz Kulessa; Alejandro Molina 001; Carsten Binnig; Benjamin Hilprecht; Kristian Kersting (CoRR, 2018)

Improving the Fusion of Outbreak Detection Methods with Supervised Learning. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (CIBB, 2019)

Improving Outbreak Detection with Stacking of Statistical Surveillance Methods. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (CoRR, 2019)

Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains. - Simon Bohlender; Eneldo Loza Mencía; Moritz Kulessa (DS, 2020)

DeepDB: Learn from Data, not from Queries! - Benjamin Hilprecht; Andreas Schmidt 002; Moritz Kulessa; Alejandro Molina 001; Kristian Kersting; Carsten Binnig (Proc. VLDB Endow., 2020)

Sum-Product Networks for Early Outbreak Detection of Emerging Diseases. - Moritz Kulessa; Bennet Wittelsbach; Eneldo Loza Mencía; Johannes Fürnkranz (AIME, 2021)

Combining Predictions Under Uncertainty: The Case of Random Decision Trees. - Florian Busch; Moritz Kulessa; Eneldo Loza Mencía; Hendrik Blockeel (DS, 2021)

Revisiting Non-specific Syndromic Surveillance. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (IDA, 2021)

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (Comput., 2021)

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

Data-driven Disease Surveillance - Moritz Kulessa (2022)

Tree-based dynamic classifier chains. - Eneldo Loza Mencía; Moritz Kulessa; Simon Bohlender; Johannes Fürnkranz (Mach. Learn., 2023)