Publications (A* and Q1) and pre-prints

Nikita Kornilov, David Li, Tikhon Mavrin, Aleksei Leonov, Nikita Gushchin, Evgeny Burnaev, Iaroslav Koshelev, Alexander Korotin (2025). Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs). A pre-print.

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Daniil Shlenskii, Alexander Korotin (2025). Overclocking Electrostatic Generative Models. A pre-print.

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Nikita Kornilov, Alexander Korotin (2025). On the equivalence of optimal transport problem and action matching with optimal vector fields. In RMS.

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Xavier Aramayo Carrasco, Grigory Ksenofontov, Aleksei Leonov, Iaroslav Koshelev, Alexander Korotin (2025). Entering the Era of Discrete Diffusion Models: A Benchmark for Schrödinger Bridges and Entropic Optimal Transport. A pre-print.

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Alexander Kolesov, Manukhov Stepan, Vladimir Palyulin, Alexander Korotin (2025). Electric Currents for Discrete Data Generation. A pre-print.

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Milena Gazdieva, Petr Mokrov, Litu Rout, Alexander Korotin, Andrey Kravchenko, Alexander Filippov, Evgeny Burnaev (2025). An optimal transport perspective on unpaired image super-resolution. In JOTA.

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Daniil Selikhanovych, David Li, Alexey Leonov, Nikita Gushchin, Sergei Kushneriuk, Alexander Filippov, Evgeny Burnaev, Iaroslav Koshelev, Alexander Korotin (2025). One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation. A pre-print.

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Nikita Gushchin, David Li, Daniil Selikhanovych, Evgeny Burnaev, Dmitry Baranchuk, Alexander Korotin (2025). Inverse Bridge Matching Distillation. In ICML 2025.

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Alexander Kolesov, Manukhov Stepan, Vladimir Palyulin, Alexander Korotin (2025). Field Matching: an Electrostatic Paradigm to Generate and Transfer Data. In ICML 2025.

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Grigory Ksenofontov, Alexander Korotin (2025). Categorical Schrodinger Bridge Matching. In ICML 2025.

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Mikhail Persiianov, Jiawei Chen, Petr Mokrov, Alexander Tyurin, Evgeny Burnaev, Alexander Korotin (2025). Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme. A pre-print.

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Manukhov Stepan, Alexander Kolesov, Vladimir Palyulin, Alexander Korotin (2025). Interaction Field Matching: Overcoming Limitations of Electrostatic Models. A pre-print.

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Milena Gazdieva, Jaemoo Choi, Alexander Kolesov, Jaewoong Choi, Alexander Korotin (2025). Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport. In ICLR 2025.

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Sergei Kholkin, Ivan Butakov, Evgeny Burnaev, Nikita Gushchin, Alexander Korotin (2025). InfoBridge: Mutual Information estimation via Bridge Matching. A pre-print.

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Roman Tarasov, Petr Mokrov, Milena Gazdieva, Evgeny Burnaev, Alexander Korotin (2025). A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers. A pre-print.

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Mikhail Persiianov, Arip Asadulaev, Nikita Andreev, Nikita Starodubcev, Dmitry Baranchuk, Anastasis Kratsios, Evgeny Burnaev, Alexander Korotin (2024). Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization. A pre-print.

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Sergei Kholkin, Grigory Ksenofontov, David Li, Nikita Kornilov, Nikita Gushchin, Alexandra Suvorikova, Alexey Kroshnin, Evgeny Burnaev, Alexander Korotin (2024). Diffusion and adversarial schrodinger bridges via iterative proportional markovian fitting. A pre-print.

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Milena Gazdieva, Arip Asadulaev, Evgeny Burnaev, Alexander Korotin (2024). Light Unbalanced Optimal Transport. In NeurIPS 2024.

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Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Anastasis Kratsios, Evgeny Burnaev, Alexander Korotin (2024). Energy-Guided Continuous Entropic Barycenter Estimation for General Costs. In NeurIPS 2024 (Spotlight, Top 25%).

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Arip Asadulaev, Rostislav Korst, Alexander Korotin, Vage Egiazarian, Andrey Filchenkov, Evgeny Burnaev (2024). Rethinking Optimal Transport in Offline Reinforcement Learning. In NeurIPS 2024.

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Nikita Gushchin, Sergey Kholkin, Evgeny Burnaev, Alexander Korotin (2024). Light and Optimal Schrodinger Bridge Matching. In ICML 2024.

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Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Evgeny Burnaev, Alexander Korotin (2024). Estimating Barycenters of Distributions with Neural Optimal Transport. In ICML 2024.

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Xavier Aramayo Carrasco, Maksim Nekrashevich, Petr Mokrov, Evgeny Burnaev, Alexander Korotin (2024). Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem. A pre-print.

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Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev (2024). Neural Optimal Transport with General Cost Functionals. In ICLR 2024.

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Alexander Korotin, Nikita Gushchin, Evgeny Burnaev (2024). Light Schrödinger Bridge. In ICLR 2024.

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Petr Mokrov, Alexander Korotin, Alexander Kolesov, Nikita Gushchin, Evgeny Burnaev (2024). Energy-guided Entropic Neural Optimal Transport. In ICLR 2024.

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Nikita Gushchin, Daniil Selikhanovych, Sergey Kholkin, Evgeny Burnaev, Alexander Korotin (2024). Adversarial Schrödinger Bridge Matching. In NeurIPS 2024.

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Nikita Kornilov, Petr Mokrov, Alexander Gasnikov, Alexander Korotin (2024). Optimal Flow Matching - Learning Straight Trajectories in Just One Step. In NeurIPS 2024.

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Milena Gazdieva, Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev (2023). Extremal Domain Translation with Neural Optimal Transport. In NeurIPS 2023.

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Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry Vetrov, Evgeny Burnaev (2023). Entropic Neural Optimal Transport via Diffusion Processes. In NeurIPS 2023 (Oral, Top 3%).

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Nikita Gushchin, Alexander Kolesov, Petr Mokrov, Polina Karpikova, Andrei Spiridonov, Evgeny Burnaev, Alexander Korotin (2023). Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark. In NeurIPS 2023.

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Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev (2023). Neural Optimal Transport. In ICLR 2023 (Spotlight, Top 25%).

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Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev (2023). Kernel Neural Optimal Transport. In ICLR 2023.

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Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev (2022). Wasserstein Iterative Networks for Barycenter Estimation. In NeurIPS 2022.

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Alexander Korotin, Alexander Kolesov, Evgeny Burnaev (2022). Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?. In NeurIPS 2022.

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Simon Abramov, Alexander Korotin, Andrey Somov, Evgeny Burnaev, Anton Stepanov, Dmitry Nikolaev, Maria A Titova (2022). Analysis of video game players’ emotions and team performance: An esports tournament case study. In IEEE Journal of Biomedical and Health Informatics.

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Litu Rout, Alexander Korotin, Evgeny Burnaev (2022). Generative Modeling with Optimal Transport Maps. In ICLR 2022.

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Alexander Korotin, Vladimir Vyugin, Evgeny Burnaev (2021). Mixability of integral losses: A key to efficient online aggregation of functional and probabilistic forecasts. In Pattern Recognition.

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Alexander Korotin, Vladimir Vyugin, Evgeny Burnaev (2021). Adaptive Hedging under Delayed Feedback. In Neurocomputing.

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Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev (2021). Manifold Topology Divergence: a Framework for Comparing Data Manifolds. In NeurIPS 2021.

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Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin Solomon, Evgeny Burnaev (2021). Large-Scale Wasserstein Gradient Flows. In NeurIPS 2021.

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Alexander Korotin, Lingxiao Li, Aude Genevay, Justin Solomon, Alexander Filippov, Evgeny Burnaev (2021). Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark. In NeurIPS 2021.

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Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev (2021). Wasserstein-2 Generative Networks. In ICLR 2021.

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Alexander Korotin, Lingxiao Li, Justin Solomon, Evgeny Burnaev (2021). Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization. In ICLR 2021.

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Alexander Korotin, Vladimir Vyugin, Evgeny Burnaev (2020). Online algorithm for aggregating experts predictions with unbounded quadratic loss. In Russian Mathematical Surveys.

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