The EFS-Server: A Web-Application for Feature Selection in Binary Classification. - Ursula Neumann; Dominik Heider (KDWeb, 2016)

Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach. - Ursula Neumann; Mona Riemenschneider; Jan-Peter Sowa; Theodor Baars; Julia Kälsch; Ali Canbay; Dominik Heider (BioData Min., 2016)

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)

EFS: an ensemble feature selection tool implemented as R-package and web-application. - Ursula Neumann; Nikita Genze; Dominik Heider (BioData Min., 2017)

Stability and Accuracy Analysis of a Feature Selection Ensemble for Binary Classification in Biomedical Datasets. - Ursula Neumann (2018)

FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration. - Lukas Pfannschmidt; Christina Göpfert; Ursula Neumann; Dominik Heider; Barbara Hammer (CIBCB, 2019)

Phi-Delta-Diagrams: Software Implementation of a Visual Tool for Assessing Classifier and Feature Performance. - Giuliano Armano; Alessandro Giuliani; Ursula Neumann; Nikolas Rothe; Dominik Heider (Mach. Learn. Knowl. Extr., 2019)

Introducing ProsperNN - a Python package for forecasting with neural networks. - Nico Beck; Julia Schemm; Claudia Ehrig; Benedikt Sonnleitner; Ursula Neumann; Hans-Georg Zimmermann (PeerJ Comput. Sci., 2024)