Alexander Korotin

research

∙ 06/16/2023

Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark

Over the last several years, there has been a significant progress in de...

6 Nikita Gushchin, et al. ∙

research

∙ 04/12/2023

Energy-guided Entropic Neural Optimal Transport

Energy-Based Models (EBMs) are known in the Machine Learning community f...

9 Petr Mokrov, et al. ∙

research

∙ 03/14/2023

Partial Neural Optimal Transport

We propose a novel neural method to compute partial optimal transport (O...

5 Milena Gazdieva, et al. ∙

research

∙ 03/10/2023

Neural Gromov-Wasserstein Optimal Transport

We present a scalable neural method to solve the Gromov-Wasserstein (GW)...

4 Maksim Nekrashevich, et al. ∙

research

∙ 01/30/2023

Extremal Domain Translation with Neural Optimal Transport

We propose the extremal transport (ET) which is a mathematical formaliza...

2 Milena Gazdieva, et al. ∙

research

∙ 11/02/2022

Entropic Neural Optimal Transport via Diffusion Processes

We propose a novel neural algorithm for the fundamental problem of compu...

6 Nikita Gushchin, et al. ∙

research

∙ 06/15/2022

Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?

Wasserstein Generative Adversarial Networks (WGANs) are the popular gene...

4 Alexander Korotin, et al. ∙

research

∙ 05/30/2022

Connecting adversarial attacks and optimal transport for domain adaptation

We present a novel algorithm for domain adaptation using optimal transpo...

0 Arip Asadulaev, et al. ∙

research

∙ 05/30/2022

Neural Optimal Transport with General Cost Functionals

We present a novel neural-networks-based algorithm to compute optimal tr...

0 Arip Asadulaev, et al. ∙

research

∙ 05/30/2022

Kernel Neural Optimal Transport

We study the Neural Optimal Transport (NOT) algorithm which uses the gen...

0 Alexander Korotin, et al. ∙

research

∙ 02/02/2022

Unpaired Image Super-Resolution with Optimal Transport Maps

Real-world image super-resolution (SR) tasks often do not have paired da...

0 Milena Gazdieva, et al. ∙

research

∙ 01/28/2022

Wasserstein Iterative Networks for Barycenter Estimation

Wasserstein barycenters have become popular due to their ability to repr...

0 Alexander Korotin, et al. ∙

research

∙ 01/28/2022

Neural Optimal Transport

We present a novel neural-networks-based algorithm to compute optimal tr...

0 Alexander Korotin, et al. ∙

research

∙ 10/06/2021

Generative Modeling with Optimal Transport Maps

With the discovery of Wasserstein GANs, Optimal Transport (OT) has becom...

0 Litu Rout, et al. ∙

research

∙ 06/08/2021

Manifold Topology Divergence: a Framework for Comparing Data Manifolds

We develop a framework for comparing data manifolds, aimed, in particula...

0 Serguei Barannikov, et al. ∙

research

∙ 06/03/2021

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark

Despite the recent popularity of neural network-based solvers for optima...

0 Alexander Korotin, et al. ∙

research

∙ 06/01/2021

Large-Scale Wasserstein Gradient Flows

Wasserstein gradient flows provide a powerful means of understanding and...

0 Petr Mokrov, et al. ∙

research

∙ 02/02/2021

Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization

Wasserstein barycenters provide a geometric notion of the weighted avera...

0 Alexander Korotin, et al. ∙

research

∙ 12/31/2020

Topological obstructions in neural networks learning

We apply methods of topological data analysis to loss functions to gain ...

0 Serguei Barannikov, et al. ∙

research

∙ 12/15/2019

Integral Mixabilty: a Tool for Efficient Online Aggregation of Functional and Probabilistic Forecasts

In this paper we extend the setting of the online prediction with expert...

0 Alexander Korotin, et al. ∙

research

∙ 11/29/2019

Barcodes as summary of objective function's topology

We apply the canonical forms (barcodes) of gradient Morse complexes to e...

0 Serguei Barannikov, et al. ∙

research

∙ 09/28/2019

Wasserstein-2 Generative Networks

Modern generative learning is mainly associated with Generative Adversar...

0 Alexander Korotin, et al. ∙

research

∙ 08/18/2019

Sensors and Game Synchronization for Data Analysis in eSports

eSports industry has greatly progressed within the last decade in terms ...

0 Anton Stepanov, et al. ∙

research

∙ 08/18/2019

Towards Understanding of eSports Athletes' Potentialities: The Sensing System for Data Collection and Analysis

eSports is a developing multidisciplinary research area. At present, the...

0 Alexander Korotin, et al. ∙

research

∙ 06/04/2019

Visual Fixations Duration as an Indicator of Skill Level in eSports

Using highly interactive systems like computer games requires a lot of v...

0 Boris B. Velichkovsky, et al. ∙

research

∙ 02/27/2019

Adaptive Hedging under Delayed Feedback

The article is devoted to investigating the application of hedging strat...

0 Alexander Korotin, et al. ∙

research

∙ 12/07/2018

Esports Athletes and Players: a Comparative Study

We present a comparative study of the players' and professional athletes...

0 Nikita Khromov, et al. ∙

research

∙ 03/18/2018

Aggregating Strategies for Long-term Forecasting

The article is devoted to investigating the application of aggregating a...

0 Alexander Korotin, et al. ∙

research

∙ 11/08/2017

Long-Term Sequential Prediction Using Expert Advice

For the prediction with expert advice setting, we consider methods to co...

0 Eugeny Burnaev, et al. ∙

Alexander Korotin

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