Differentially Private Learning from Label Proportions. - Timon Sachweh; Daniel Boiar; Thomas Liebig (PKDD/ECML Workshops (1), 2021)

Distributed LSTM-Learning from Differentially Private Label Proportions. - Timon Sachweh; Daniel Boiar; Thomas Liebig (ICDM (Workshops), 2022)

Forecasting Algae Growth in Photo-Bioreactors Using Attention LSTMs. - Daniel Boiar; Nils Killich; Lukas Schulte; Victor Hernandez Moreno; Jochen Deuse; Thomas Liebig (SEFM Workshops, 2022)

LOSDD: Leave-Out Support Vector Data Description for Outlier Detection. - Daniel Boiar; Thomas Liebig; Erich Schubert (CoRR, 2022)

A Cost-Efficient Robotic Through-Hole Assembly System for Dual-Pin Component Insertion. - Mikhail Polikarpov; Yousuf Mehmood; Daniel Boiar; Lukas Schulte; Jochen Deuse (ICCMA, 2023)