18 citations · 98 across the 27 of their papers we have counts for
8 papers · 1 filter
Entropic Neural Optimal Transport via Diffusion Processes
Nikita Gushchin, Alexander Kolesov, Alexander Korotin +2
We propose a novel neural algorithm for the fundamental problem of computing the entropic optimal transport (EOT) plan between continuous probability distributions which are access…
Connecting adversarial attacks and optimal transport for domain adaptation
Arip Asadulaev, Vitaly Shutov, Alexander Korotin +2
We present a novel algorithm for domain adaptation using optimal transport. In domain adaptation, the goal is to adapt a classifier trained on the source domain samples to the targ…
Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?
Alexander Korotin, Alexander Kolesov, Evgeny Burnaev
Wasserstein Generative Adversarial Networks (WGANs) are the popular generative models built on the theory of Optimal Transport (OT) and the Kantorovich duality. Despite the success…
Neural Optimal Transport with General Cost Functionals
Arip Asadulaev, Alexander Korotin, Vage Egiazarian +2
We introduce a novel neural network-based algorithm to compute optimal transport (OT) plans for general cost functionals. In contrast to common Euclidean costs, i.e., or $…
Kernel Neural Optimal Transport
Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev
We study the Neural Optimal Transport (NOT) algorithm which uses the general optimal transport formulation and learns stochastic transport plans. We show that NOT with the weak qua…
An Optimal Transport Perspective on Unpaired Image Super-Resolution
Milena Gazdieva, Petr Mokrov, Litu Rout +4
Real-world image super-resolution (SR) tasks often do not have paired datasets, which limits the application of supervised techniques. As a result, the tasks are usually approached…
Wasserstein Iterative Networks for Barycenter Estimation
Alexander Korotin, Vage Egiazarian, Lingxiao Li +1
Wasserstein barycenters have become popular due to their ability to represent the average of probability measures in a geometrically meaningful way. In this paper, we present an al…
Neural Optimal Transport
Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev
We present a novel neural-networks-based algorithm to compute optimal transport maps and plans for strong and weak transport costs. To justify the usage of neural networks, we prov…