Fair pairwise learning to rank. - Mattia Cerrato; Marius Köppel; Alexander Segner; Roberto Esposito; Stefan Kramer 001 (DSAA, 2020)

Ranking Creative Language Characteristics in Small Data Scenarios. - Julia Siekiera; Marius Köppel; Edwin Simpson; Kevin Stowe; Iryna Gurevych; Stefan Kramer 001 (ICCC, 2022)

Fair Group-Shared Representations with Normalizing Flows. - Mattia Cerrato; Marius Köppel; Alexander Segner; Stefan Kramer 001 (CoRR, 2022)

Fair Interpretable Learning via Correction Vectors. - Mattia Cerrato; Marius Köppel; Alexander Segner; Stefan Kramer 001 (CoRR, 2022)

Fair Interpretable Representation Learning with Correction Vectors. - Mattia Cerrato; Alesia Vallenas Coronel; Marius Köppel; Alexander Segner; Roberto Esposito; Stefan Kramer 001 (CoRR, 2022)

Invariant Representations with Stochastically Quantized Neural Networks. - Mattia Cerrato; Marius Köppel; Roberto Esposito; Stefan Kramer 001 (AAAI, 2023)

The Case for Correctability in Fair Machine Learning. - Mattia Cerrato; Alesia Vallenas Coronel; Marius Köppel (EWAF, 2023)

Google Topics as a Way Out of the Cookie Dilemma? - Marius Köppel; Jan-Philipp Muttach; Gerrit Hornung (PKDD/ECML Workshops (1), 2023)

Google Topics als Ausweg aus dem Cookie-Dilemma? - Rechtliche Anforderungen an die technische Alternative zur individualisierten Werbung im Internet. - Jan-Philipp Muttach; Marius Köppel; Gerrit Hornung (Comput. und Recht, 2023)

Trust in Fair Algorithms: Pilot Experiment. - Mattia Cerrato; Marius Köppel; Kiara Stempel; Alesia Vallenas Coronel; Niklas Witzig (EWAF, 2024)

Can machine learning solve the challenge of adaptive learning and the individualization of learning paths? A field experiment in an online learning platform. - Tim Klausmann; Marius Köppel; Daniel Schunk; Isabell Zipperle (CoRR, 2024)

10 Years of Fair Representations: Challenges and Opportunities. - Mattia Cerrato; Marius Köppel; Philipp Wolf; Stefan Kramer 001 (CoRR, 2024)

Predicting NOx emissions in Biochar Production Plants using Machine Learning. - Marius Köppel; Niklas Witzig; Tim Klausmann; Mattia Cerrato; Tobias Schweitzer; Jochen Weber 004; Erdem Yilmaz; Juan Chimbo; Bernardo del Campo; Lissete Davila; David Barreno (CoRR, 2024)

Stochastic Fairness Interventions Are Arbitrary. - Mattia Cerrato; Marius Köppel; Kiara Stempel; Philipp Wolf; Stefan Kramer 001 (EWAF, 2025)

Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance. - Marius Köppel; Alexander Segner; Martin Wagener; Lukas Pensel; Andreas Karwath; Stefan Kramer 001 (Mach. Learn., 2025)