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StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation
P. 2184–2194.
Воронова К. Д., Lyadova L. N., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4 P. 153–170
Title: Automated Event Logs Generation Based on Unstructured Internet Sources for Process Analysis Tasks
Abstract. This paper presents an approach to automated structuring event-related information extracted from unstructured textual Internet sources for process mining tasks. In many practical cases, information on events associated with various processes is not presented in the form of ready-made event logs, but is ...
Added: September 14, 2026
Ali S., Bocharnikov V., Ratnikov F. et al., Sensors 2026 Vol. 26 No. 16 Article 5024
Large distributed sensor arrays require repeated recalibration as radiation damage, material aging, gain variation, and readout drift alter channel responses. We studied a high-granularity calorimeter as a large sensor array and addressed unsupervised recalibration from two unpaired datasets: a nominal reference response and an aged response with attenuated cell-wise signals. Aging was modeled by a ...
Added: August 11, 2026
Glazkova A., Lyashevskaya O., Morozov D. et al., Journal of Mathematical Sciences 2025 Vol. 546 P. 32–47
This paper addresses the task of lemmatizing abbreviations in the Russian language. Abbreviation lemmatization is particularly challenging, as it involves not only transforming a word into its normal form but also correctly expanding the abbreviation. We explore two approaches to this task, both leveraging large pretrained language models. The first approach is generative, where the ...
Added: March 10, 2026
Телешева Э. Д., Hushchyn M., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2025 Т. 527 № S С. 388–399
he problem of generating high-quality synthetic data is crucial for many data science tasks. A generated dataset can cut the costs on the augmentation of the existing data with additional instances, for example, in physics, or help with its privacy protection, for instance, in banking. However, generating a tabular dataset is challenging, as the data ...
Added: February 12, 2026
Morozov N., Maximov I., Tiapkin D. et al., , in: Volume 267: International Conference on Machine Learning, 13-19 July 2025, Vancouver Convention Center, Vancouver, CanadaVol. 267.: [б.и.], 2025. P. 44887–44910.
Generative Flow Networks (GFlowNets) are a family of generative models that learn to sample objects from a given probability distribution, potentially known up to a normalizing constant. Instead of working in the object space, GFlowNets proceed by sampling trajectories in an appropriately constructed directed acyclic graph environment, greatly relying on the acyclicity of the graph. ...
Added: October 15, 2025
Maksimenkova O. V., Сегал А. П., Вопросы философии 2025 № 10 С. 67–76
The study is devoted to the humans and artificial intelligence (AI) interaction. The authors view this interaction as mediated by interfaces that both simplify it and hide the real mechanisms of encoding and decoding messages (according to Shannon). In such a situation, the characteristics of the actor of communication are blurred, and it is not ...
Added: October 2, 2025
Cham: Springer, 2025.
This book constitutes the refereed proceedings of 34th International Workshops which were held in conjunction with the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025.
The 20 full papers and 8 abstracts included in this workshop volume were carefully reviewed and selected from 42 submissions. ...
Added: September 29, 2025
Golyadkin M., Saraev S., Makarov I., IEEE Access 2025 Vol. 13 P. 7526–7537
Manga colorization in augmented reality (AR) environments presents unique challenges, particularly when colorizing manga pages captured in photos under various real-world conditions. Testing models in AR settings for manga colorization has been a significant challenge, primarily because of the absence of suitable datasets tailored for this task. To address this, we propose a benchmark for ...
Added: April 29, 2025
Golyadkin M., Saraev S., Makarov I., , in: 2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct).: IEEE, 2024. P. 608–611.
This paper introduces an innovative approach to manga colorization within augmented reality (AR) environments, focusing on the unique challenges posed by colorizing photos of manga books. We present a novel method using diffusion models to generate a synthetic dataset that accurately replicates photographed manga pages. Additionally, we have compiled a dataset of real manga photographs, ...
Added: April 29, 2025
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
Denis Kuznedelev, Valerii Startsev, Daniil Shlenskii et al., , in: The Thirteenth International Conference on Learning Representations: ICLR 2025.: ICLR, 2025. P. 1–30.
There is a prevalent opinion that diffusion-based models outperform GAN-based counterparts in the Image Super Resolution (ISR) problem. However, in most studies, diffusion-based ISR models employ larger networks and are trained longer than the GAN baselines. This raises the question of whether the high performance stems from the superiority of the diffusion paradigm or if ...
Added: February 10, 2025
Gorshkov S., Ignatov D. I., Chernysheva A. et al., IEEE Access 2025 Vol. 13 P. 962–979
Identifying potentially high-performing students is crucial for universities aiming to enhance educational outcomes, for companies seeking to recruit top talents early, and for advertising platforms looking to optimize targeted marketing. This paper introduces an algorithm designed to identify students with exceptional academic performance by analyzing their subscriptions to communities on the social network VKontakte. The ...
Added: January 3, 2025
Bogolepova S., Жаркова М. Г., Отечественная и зарубежная педагогика 2024 Т. 1 № 5(101) С. 123–137
In the era of rapid development of generative language models these tools are increasingly being used by both students and instructors. This paper aims to investigate the potential of generative models interacting with users via chatbots ChatGPT и PerplexityAI for the evaluation of standardised essays in English and the provision of feedback on their quality. ...
Added: October 28, 2024
Bobkov D., Titov V., Alanov A. et al., , in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.: IEEE, 2024. P. 9337–9346.
The task of manipulating real image attributes through StyleGAN inversion has been extensively researched. This process involves searching latent variables from a well-trained StyleGAN generator that can synthesize a real image modifying these latent variables and then synthesizing an image with the desired edits. A balance must be struck between the quality of the reconstruction ...
Added: July 10, 2024
Rogachev A., Ratnikov F., Computing and Software for Big Science 2024 Vol. 8 No. 1 Article 12
In this paper, we explore the use of Generative Adversarial Networks (GANs) to speed up the simulation process while ensuring that the generated results are consistent in terms of physics metrics. Our main focus is the application of spectral normalization for GANs to generate electromagnetic calorimeter (ECAL) response data, which is a crucial component of ...
Added: July 2, 2024
Tiapkin D., Morozov N., Naumov A. 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. 4213–4221.
The recently proposed generative flow networks (GFlowNets) are a method of training a policy to sample compositional discrete objects with probabilities proportional to a given reward via a sequence of actions. GFlowNets exploit the sequential nature of the problem, drawing parallels with reinforcement learning (RL). Our work extends the connection between RL and GFlowNets to ...
Added: June 22, 2024
Rogachev A., Ratnikov F., EPJ Web of Conferences 2024 Vol. 295 Article 09007
High energy physics experiments heavily rely on the results of MC simulation of data used to extract physics results. However, the detailed simulation often requires tremendous amount of computation resources.
Using Generative Adversarial Networks and other deep learning generative techniques can drastically speed up the computationally heavy simulations like a simulation of the calorimeter response. To ...
Added: May 20, 2024
Pavel Latyshev, Fedor Pavlov, Herbert A. et al., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.
Added: December 1, 2023