NetGAN without GAN: From Random Walks to Low-Rank Approximations. - Luca Rendsburg; Holger Heidrich; Ulrike von Luxburg (ICML, 2020)

Tangles: From Weak to Strong Clustering. - Christian Elbracht; Diego Fioravanti; Solveig Klepper; Jakob Kneip; Luca Rendsburg; Maximilian Teegen; Ulrike von Luxburg (CoRR, 2020)

Comparison-based centrality measures. - Luca Rendsburg; Damien Garreau (Int. J. Data Sci. Anal., 2021)

Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference. - Luca Rendsburg; Agustinus Kristiadi; Philipp Hennig; Ulrike von Luxburg (AISTATS, 2022)

Interpolation and Regularization for Causal Learning. - Leena Chennuru Vankadara; Luca Rendsburg; Ulrike von Luxburg; Debarghya Ghoshdastidar (NeurIPS, 2022)

A Consistent Estimator for Confounding Strength. - Luca Rendsburg; Leena Chennuru Vankadara; Debarghya Ghoshdastidar; Ulrike von Luxburg (CoRR, 2022)

Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees. - Solveig Klepper; Christian Elbracht; Diego Fioravanti; Jakob Kneip; Luca Rendsburg; Maximilian Teegen; Ulrike von Luxburg (J. Mach. Learn. Res., 2023)

Inductive Bias in Machine Learning. - Luca Rendsburg (2023)