Uncertainty Estimates for Ordinal Embeddings. - Michael Lohaus; Philipp Hennig; Ulrike von Luxburg (CoRR, 2019)

Too Relaxed to Be Fair. - Michael Lohaus; Michaël Perrot; Ulrike von Luxburg (ICML, 2020)

Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. - Dominik Zietlow; Michael Lohaus; Guha Balakrishnan; Matthäus Kleindessner; Francesco Locatello; Bernhard Schölkopf; Chris Russell 001 (CVPR, 2022)

Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. - Michael Lohaus; Matthäus Kleindessner; Krishnaram Kenthapadi; Francesco Locatello; Chris Russell 001 (NeurIPS, 2022)

Limitations of Fairness in Machine Learning - Michael Lohaus (2022)

Insights into Ordinal Embedding Algorithms: A Systematic Evaluation. - Leena Chennuru Vankadara; Michael Lohaus; Siavash Haghiri; Faiz Ul Wahab; Ulrike von Luxburg (J. Mach. Learn. Res., 2023)