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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...
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04/12/2023
Energy-guided Entropic Neural Optimal Transport
Energy-Based Models (EBMs) are known in the Machine Learning community f...
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03/14/2023
Partial Neural Optimal Transport
We propose a novel neural method to compute partial optimal transport (O...
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03/10/2023
Neural Gromov-Wasserstein Optimal Transport
We present a scalable neural method to solve the Gromov-Wasserstein (GW)...
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01/30/2023
Extremal Domain Translation with Neural Optimal Transport
We propose the extremal transport (ET) which is a mathematical formaliza...
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11/02/2022
Entropic Neural Optimal Transport via Diffusion Processes
We propose a novel neural algorithm for the fundamental problem of compu...
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06/15/2022
Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?
Wasserstein Generative Adversarial Networks (WGANs) are the popular gene...
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05/30/2022
Connecting adversarial attacks and optimal transport for domain adaptation
We present a novel algorithm for domain adaptation using optimal transpo...
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05/30/2022
Neural Optimal Transport with General Cost Functionals
We present a novel neural-networks-based algorithm to compute optimal tr...
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05/30/2022
Kernel Neural Optimal Transport
We study the Neural Optimal Transport (NOT) algorithm which uses the gen...
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02/02/2022
Unpaired Image Super-Resolution with Optimal Transport Maps
Real-world image super-resolution (SR) tasks often do not have paired da...
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01/28/2022
Wasserstein Iterative Networks for Barycenter Estimation
Wasserstein barycenters have become popular due to their ability to repr...
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01/28/2022
Neural Optimal Transport
We present a novel neural-networks-based algorithm to compute optimal tr...
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10/06/2021
Generative Modeling with Optimal Transport Maps
With the discovery of Wasserstein GANs, Optimal Transport (OT) has becom...
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06/08/2021
Manifold Topology Divergence: a Framework for Comparing Data Manifolds
We develop a framework for comparing data manifolds, aimed, in particula...
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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...
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06/01/2021
Large-Scale Wasserstein Gradient Flows
Wasserstein gradient flows provide a powerful means of understanding and...
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02/02/2021
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Wasserstein barycenters provide a geometric notion of the weighted avera...
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12/31/2020
Topological obstructions in neural networks learning
We apply methods of topological data analysis to loss functions to gain ...
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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...
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11/29/2019
Barcodes as summary of objective function's topology
We apply the canonical forms (barcodes) of gradient Morse complexes to e...
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09/28/2019
Wasserstein-2 Generative Networks
Modern generative learning is mainly associated with Generative Adversar...
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08/18/2019
Sensors and Game Synchronization for Data Analysis in eSports
eSports industry has greatly progressed within the last decade in terms ...
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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...
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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...
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02/27/2019
Adaptive Hedging under Delayed Feedback
The article is devoted to investigating the application of hedging strat...
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12/07/2018
Esports Athletes and Players: a Comparative Study
We present a comparative study of the players' and professional athletes...
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03/18/2018
Aggregating Strategies for Long-term Forecasting
The article is devoted to investigating the application of aggregating a...
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11/08/2017