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Neural Optimal Transport with General Cost Functionals
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Asadulaev A., Korotin A., Vage Egiazarian, Mokrov P., Evgeny Burnaev
Language:
English
Kolesnikov A., Popova S., Математические заметки 2026 Т. 119 № 3 С. 377–390
We consider the problem of optimal exchange which can be formulated as a kind of optimal transportation problem. The existence of an optimal solution and a duality theorem for the optimal exchange problem are proved in case of completely regular topological spaces. We show the connection between the problem of optimal exchange and the optimal ...
Added: March 12, 2026
Barchukov V., Lecture Notes in Networks and Systems 2021 Vol. 160 P. 713–718
The article covers the analysis of the problems of budget managing processes in municipalities. Noting the complexity and importance of this process, the author notes that one of the directions for its improvement is the use of intelligent information systems. Currently, these information systems are successfully implemented in various areas of business and management, and ...
Added: January 21, 2026
Cherednichenko O., Poptsova M., Computers in Biology and Medicine 2025 Vol. 184 Article 109440
Non-B DNA structures, or flipons, are important functional elements that regulate a large spectrum of cellular programs. Experimental technologies for flipon detection are limited to the subsets that are active at the time of an experiment and cannot capture whole-genome functional set. Thus, the task of generating reliable whole-genome annotations of non-B DNA structures is ...
Added: March 11, 2025
Bazhukov M., Voloshina E., Sergey Pletnev et al., , in: Proceedings of the 28th Conference on Computational Natural Language Learning.: Association for Computational Linguistics, 2024. P. 280–290.
Added: March 11, 2025
Gazdieva M., Alexander Korotin, Daniil Selikhanovych et al., , in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023).: Curran Associates, Inc., 2023. P. 40381–40413.
Added: January 22, 2025
Chaichuk M., Tutubalina E., Transactions of the Association for Computational Linguistics 2024
This paper introduces models developed for the ImageCLEFmed 2024 MEDVQA-GI task, aimed at leveraging text-to-image generative models to create a comprehensive dataset of artificial colonoscopy images from textual prompts. The task’s complexity arises from the novel and relatively uncharted nature of the provided training dataset, its limited size, and the specificity required in the generated ...
Added: December 13, 2024
Stefan Nikolić, Ignatov D. I., Khvorykh G. et al., PeerJ Computer Science 2024 Vol. 10 Article e2454
Despite the identification of several dozen genetic loci associated with ischemic stroke (IS), the genetic bases of this disease remain largely unexplored. In this research we present the results of genome-wide association studies (GWAS) based on classical statistical testing and machine learning algorithms (logistic regression, gradient boosting on decision trees, and tabular deep learning model ...
Added: December 11, 2024
Ramazyan T., Hushchyn M., Derkach D., , in: ECAI 2024. 27th European Conference on Artificial Intelligence, October 19 – 24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024).: IOS Press, 2024. P. 2394–2401.
We propose a new uncertainty estimator for gradient-free optimisation of black-box simulators using deep generative surrogate models. Optimisation of these simulators is especially challenging for stochastic simulators and higher dimensions. To address these issues, we utilise a deep generative surrogate approach to model the black box response for the entire parameter space. We then leverage ...
Added: December 1, 2024
Gladin E., Dvurechensky P., Mielke A. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 14484–14508.
Added: November 28, 2024
Morozov N., Rakitin D., Oleg Desheulin et al., , in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2-4 May 2024, Palau de Congressos, Valencia, Spain. PMLR: Volume 238Vol. 238.: Valencia: PMLR, 2024. P. 4852–4860.
Added: June 21, 2024
Dvinskikh D., Optimization Methods and Software 2022 Vol. 37 No. 5 P. 1603–1635
In the machine learning and optimization community, there are two main approaches for the convex risk minimization problem, namely the Stochastic Approximation (SA) and the Sample Average Approximation (SAA). In terms of the oracle complexity (required number of stochastic gradient evaluations), both approaches are considered equivalent on average (up to a logarithmic factor). The total complexity depends on ...
Added: March 27, 2024
Blumenau M., Vorobev D., Fridman M., [б.и.], 2022.
We propose a method for recognizing several types of magneto-plasma structures at the Sun, employing deep machine learning. Various neural networks (namely, fully connected, recurrent and convolutional networks) have increasingly become popular to many fields of physics involving data analysis and pattern recognition [Krizhevsky et al., 2012, NeurIPS]. Meanwhile, in solar physics, traditional algorithms relying ...
Added: February 15, 2024
Vorobev D., Blumenau M., Fridman M. et al., EGU General Assembly, 2022.
We propose a new method for automatic detection of solar magnetic tornadoes based on computer vision methods. Magnetic tornadoes are magneto-plasma structures with a swirling magnetic field in the solar corona, and there is also evidence for the rotation of plasma in them. A theoretical description and numerical modeling of these objects are very difficult ...
Added: February 15, 2024
Vorobev D., Blumenau M., Fridman M. et al., [б.и.], 2022.
We show a possibility of automated detection of solar magnetic tornadoes, using the classic computer vision and deep learning methods. We define magnetic tornadoes, independently of their origin, as magneto-plasma objects in the solar corona in which a magnetic field is twisted. Typically, a whole magnetic tornado rotates resembling tornadoes in the terrestrial atmosphere. Meanwhile, ...
Added: February 15, 2024
Khusyainov T., В кн.: Современная реальность в социально-психологическом контексте – 2023.: НГПУ, 2023. С. 139–142.
This article touches upon the problem of the influence of neural networks on the communicative practices of a modern person. With the development of technology, at the moment the number of tools available to any user of the Global Network is quite large and is constantly growing. Affecting all new areas of life, the latest developments ...
Added: October 8, 2023
Chertenkov V., Burovskiy E., Shchur L., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2023 Vol. 108 No. 3 Article L032102
We analyze the problem of supervised learning of ferromagnetic phas transitions from the statistical physics perspective. We consider two systems in two universality classes, the two-dimensional Ising model and two-dimensional Baxter-Wu model, and perform careful finite-size analysis of the results of the supervised learning of the phases of each model. We find that the variance ...
Added: September 19, 2023
M. S. I. Malik, Hussain A., Artificial Intelligence Review 2020 Vol. 53 No. 1 P. 407–427
Helpfulness of online reviews is a multi-faceted concept. The reviews are usually ranked on
the basis of perceived helpful votes and aid in making purchase decisions for online customers.
This study extends the prior work done for review helpfulness by considering not
only the influential characteristics of reviews but also incorporates influential indicators of
reviewer and product category. Influential ...
Added: November 1, 2022