Chances of Interpretable Transfer Learning for Human Activity Recognition in Warehousing. - Michael Kirchhof; Lena Schmid; Christopher Reining; Michael ten Hompel; Markus Pauly (ICCL, 2021)

pRSL: Interpretable multi-label stacking by learning probabilistic rules. - Michael Kirchhof; Lena Schmid; Christopher Reining; Michael ten Hompel; Markus Pauly (UAI, 2021)

Machine Learning for Multi-Output Regression: When should a holistic multivariate approach be preferred over separate univariate ones? - Lena Schmid; Alexander Gerharz; Andreas Groll; Markus Pauly (CoRR, 2022)

Dataset Bias in Human Activity Recognition. - Nilah Ravi Nair; Lena Schmid; Fernando Moya Rueda; Markus Pauly; Gernot A. Fink; Christopher Reining (CoRR, 2023)

Comparing statistical and machine learning methods for time series forecasting in data-driven logistics - A simulation study. - Lena Schmid; Moritz Roidl; Markus Pauly (CoRR, 2023)

Tree-based ensembles for multi-output regression: Comparing multivariate approaches with separate univariate ones. - Lena Schmid; Alexander Gerharz; Andreas Groll; Markus Pauly (Comput. Stat. Data Anal., 2023)

Representation Biases in Time-Series Human Activity Recognition with Small Sample Sizes. - Nilah Ravi Nair; Lena Schmid; Christopher Reining; Fernando Moya Rueda; Markus Pauly; Gernot A. Fink (ICPR (15), 2024)

TREE: Tree Regularization for Efficient Execution. - Lena Schmid; Daniel Biebert; Christian Hakert; Kuan-Hsun Chen; Michel Lang; Markus Pauly; Jian-Jia Chen (CoRR, 2024)