VI Bogachev, “Kantorovich problem of optimal transportation of measures: new directions of
research”, Uspekhi Mat. Nauk, 77:5(467) (2022), 3–52; Russian Math. Surveys, 77:5 (2022) …

Regularized optimal transport (OT) is now increasingly used as a loss or as a matching layer
in neural networks. Entropy-regularized OT can be computed using the Sinkhorn algorithm …

We study the stability of entropically regularized optimal transport with respect to the
marginals. Lipschitz continuity of the value and Hölder continuity of the optimal coupling in …

We derive limit distributions for various empirical regularized optimal transport quantities
between probability distributions supported on a finite metric space and show their bootstrap …

Wasserstein barycenters provide a geometrically meaningful way to aggregate probability
distributions, built on the theory of optimal transport. They are difficult to compute in practice …

We study the convergence of divergence-regularized optimal transport as the regularization
parameter vanishes. Sharp rates for general divergences including relative entropy or Lp …

В работе дан обзор исследований последнего десятилетия и приведены новые
результаты по различным новым модификациям классической задачи Канторовича …

We analyze continuous optimal transport problems in the so-called Kantorovich form, where
we seek a transport plan between two marginals that are probability measures on compact …

Understanding how cells change their identity and behaviour in living systems is an
important question in many fields of biology. The problem of inferring cell trajectories from …

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 …