The solution of inverse problems is of fundamental interest in medical and astronomical
imaging, geophysics as well as engineering and life sciences. Recent advances were made …

Maximum mean discrepancy (MMD) flows suffer from high computational costs in large
scale computations. In this paper, we show that MMD flows with Riesz kernels $ K (x, y) …

Entropy-regularized optimal transport and its multi-marginal generalization have attracted
increasing attention in various applications, in particular due to efficient Sinkhorn-like …

The aim of this paper is twofold. Based on the geometric Wasserstein tangent space, we first
introduce Wasserstein steepest descent flows. These are locally absolutely continuous …

We consider the numerical solution of the discrete multi-marginal optimal transport (MOT) by
means of the Sinkhorn algorithm. In general, the Sinkhorn algorithm suffers from the curse of …

This contribution features an accelerated computation of the Sinkhorn's algorithm, which
approximates the Wasserstein transportation distance, by employing nonequispaced fast …

This paper provides results on Wasserstein gradient flows between measures on the real
line. Utilizing the isometric embedding of the Wasserstein space P 2 (R) into the Hilbert …

Increasingly complex data analysis tasks motivate the study of the dependency of
distributions of multivariate continuous random variables on scalar or vector predictors …

In supervised learning, the regularization path is sometimes used as a convenient
theoretical proxy for the optimization path of gradient descent initialized from zero. In this …

Gromov-Wasserstein (GW) distances are combinations of Gromov-Hausdorff and
Wasserstein distances that allow the comparison of two different metric measure spaces …