activity
20182021
most citedLarge-Scale Wasserstein Gradient Flows

10 citations · 20 across the 2 of their papers we have counts for

collaborators

9 papers

cs.LG202110 cited

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

Alexander Korotin, Lingxiao Li, Aude Genevay +3

Despite the recent popularity of neural network-based solvers for optimal transport (OT), there is no standard quantitative way to evaluate their performance. In this paper, we add…

cs.LG202110 cited

Large-Scale Wasserstein Gradient Flows

Petr Mokrov, Alexander Korotin, Lingxiao Li +3

Wasserstein gradient flows provide a powerful means of understanding and solving many diffusion equations. Specifically, Fokker-Planck equations, which model the diffusion of proba…

cs.LG2019

Wasserstein-2 Generative Networks

Alexander Korotin, Vage Egiazarian, Arip Asadulaev +2

We propose a novel end-to-end non-minimax algorithm for training optimal transport mappings for the quadratic cost (Wasserstein-2 distance). The algorithm uses input convex neural…

cs.HC2019

Sensors and Game Synchronization for Data Analysis in eSports

Anton Stepanov, Andrey Lange, Nikita Khromov +3

eSports industry has greatly progressed within the last decade in terms of audience and fund rising, broadcasting, networking and hardware. Since the number and quality of professi…

cs.HC2019

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

Alexander Korotin, Nikita Khromov, Anton Stepanov +3

eSports is a developing multidisciplinary research area. At present, there is a lack of relevant data collected from real eSports athletes and lack of platforms which could be used…

cs.HC2019

Visual Fixations Duration as an Indicator of Skill Level in eSports

Boris B. Velichkovsky, Nikita Khromov, Alexander Korotin +2

Using highly interactive systems like computer games requires a lot of visual activity and eye movements. Eye movements are best characterized by visual fixation - periods of time…