Statistical guarantees for stochastic Metropolis-Hastings. - Sebastian Bieringer; Gregor Kasieczka; Maximilian F. Steffen; Mathias Trabs (CoRR, 2023)

AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization. - Sebastian Bieringer; Gregor Kasieczka; Maximilian F. Steffen; Mathias Trabs (CoRR, 2023)

Dimensionality Reduction and Wasserstein Stability for Kernel Regression. - Stephan Eckstein; Armin Iske; Mathias Trabs (J. Mach. Learn. Res., 2023)

Calibrating Bayesian Generative Machine Learning for Bayesiamplification. - Sebastian Bieringer; Sascha Diefenbacher; Gregor Kasieczka; Mathias Trabs (CoRR, 2024)

A Wasserstein perspective of Vanilla GANs. - Lea Kunkel; Mathias Trabs (Neural Networks, 2025)

On the minimax optimality of Flow Matching through the connection to kernel density estimation. - Lea Kunkel; Mathias Trabs (CoRR, 2025)