Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Budennyy, Semen"'
Despite an artificial intelligence-assisted modeling of disordered crystals is a widely used and well-tried method of new materials design, the issues of its robustness, reliability, and stability are still not resolved and even not discussed enough.
Externí odkaz:
http://arxiv.org/abs/2410.13873
The study of the stock market with the attraction of machine learning approaches is a major direction for revealing hidden market regularities. This knowledge contributes to a profound understanding of financial market dynamics and getting behavioura
Externí odkaz:
http://arxiv.org/abs/2303.14221
Cardiovascular disease remains a significant problem in modern society. Among non-invasive techniques, the electrocardiogram (ECG) is one of the most reliable methods for detecting abnormalities in cardiac activities. However, ECG interpretation requ
Externí odkaz:
http://arxiv.org/abs/2303.11429
Autor:
Tuganova, Regina, Permyakova, Anna, Kuznetsova, Anna, Rakhmanova, Karina, Monzul, Natalia, Uvarov, Roman, Kovtun, Elizaveta, Budennyy, Semen
Green technology is viewed as a means of creating a sustainable society and a catalyst for sustainable development by the global community. It is responsible for both the potential reduction of production waste and the reduction of carbon footprint a
Externí odkaz:
http://arxiv.org/abs/2210.09611
Pharmaceutical companies operate in a strictly regulated and highly risky environment in which a single slip can lead to serious financial implications. Accordingly, the announcements of clinical trial results tend to determine the future course of e
Externí odkaz:
http://arxiv.org/abs/2208.07248
Autor:
Korovin, Alexey, Vasilyev, Artem, Egorov, Fedor, Saykin, Dmitry, Terukov, Evgeny, Shakhray, Igor, Zhukov, Leonid, Budennyy, Semen
Efficient defect detection in solar cell manufacturing is crucial for stable green energy technology manufacturing. This paper presents a deep-learning-based automatic detection model SeMaCNN for classification and semantic segmentation of electrolum
Externí odkaz:
http://arxiv.org/abs/2208.05994
Autor:
Budennyy, Semen, Lazarev, Vladimir, Zakharenko, Nikita, Korovin, Alexey, Plosskaya, Olga, Dimitrov, Denis, Arkhipkin, Vladimir, Oseledets, Ivan, Barsola, Ivan, Egorov, Ilya, Kosterina, Aleksandra, Zhukov, Leonid
The size and complexity of deep neural networks continue to grow exponentially, significantly increasing energy consumption for training and inference by these models. We introduce an open-source package eco2AI to help data scientists and researchers
Externí odkaz:
http://arxiv.org/abs/2208.00406
Autor:
Korovin, Alexey N., Humonen, Innokentiy S., Samtsevich, Artem I., Eremin, Roman A., Vasilyev, Artem I., Lazarev, Vladimir D., Budennyy, Semen A.
Publikováno v:
Materials Today Chemistry 2023, 30, 101541
The discovery of new catalysts is one of the significant topics of computational chemistry as it has the potential to accelerate the adoption of renewable energy sources. Recently developed deep learning approaches such as graph neural networks (GNNs
Externí odkaz:
http://arxiv.org/abs/2207.05013
Autor:
Yudin, Dmitry, Zakharenko, Nikita, Smetanin, Artem, Filonov, Roman, Kichik, Margarita, Kuznetsov, Vladislav, Larichev, Dmitry, Gudov, Evgeny, Budennyy, Semen, Panov, Aleksandr
Publikováno v:
In Engineering Applications of Artificial Intelligence February 2024 128
Autor:
Eremin, Roman A., Humonen, Innokentiy S., Kazakov, Alexey A., Lazarev, Vladimir D., Pushkarev, Anatoly P., Budennyy, Semen A.
Publikováno v:
In Computational Materials Science 25 January 2024 232