| Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights AV Emelyanov, KE Nikiruy, AV Serenko, AV Sitnikov, MY Presnyakov, ... Nanotechnology 31 (4), 045201, 2019 | 99 | 2019 |
| Machine learning models of text categorization by author gender using topic-independent features A Sboev, T Litvinova, D Gudovskikh, R Rybka, I Moloshnikov Procedia Computer Science 101, 135-142, 2016 | 83 | 2016 |
| Automatic gender identification of author of Russian text by machine learning and neural net algorithms in case of gender deception A Sboev, I Moloshnikov, D Gudovskikh, A Selivanov, R Rybka, T Litvinova Procedia computer science 123, 417-423, 2018 | 38 | 2018 |
| Analytical properties of the perturbed FitzHugh–Nagumo model NA Kudryashov, RB Rybka, AG Sboev Applied Mathematics Letters 76, 142-147, 2018 | 34 | 2018 |
| Solving a classification task by spiking neural network with STDP based on rate and temporal input encoding A Sboev, A Serenko, R Rybka, D Vlasov Mathematical Methods in the Applied Sciences 43 (13), 7802-7814, 2020 | 29 | 2020 |
| Deep Learning neural nets versus traditional machine learning in gender identification of authors of RusProfiling texts A Sboev, I Moloshnikov, D Gudovskikh, A Selivanov, R Rybka, T Litvinova Procedia computer science 123, 424-431, 2018 | 27 | 2018 |
| Современные подходы к моделированию активности культур нейронов in vitro КВ Анохин, МС Бурцев, ВА Ильин, ИИ Киселев, КА Кукин, КВ Лахман, ... Математическая биология и биоинформатика 7 (2), 372-397, 2012 | 23 | 2012 |
| Solving a classification task by spiking neurons with STDP and temporal coding A Sboev, D Vlasov, R Rybka, A Serenko Procedia computer science 123, 494-500, 2018 | 22 | 2018 |
| Deep learning network models to categorize texts according to author's gender and to identify text sentiment A Sboev, T Litvinova, I Voronina, D Gudovskikh, R Rybka 2016 International Conference on Computational Science and Computational …, 2016 | 22 | 2016 |
| A quantitative method of text emotiveness evaluation on base of the psycholinguistic markers founded on morphological features A Sboev, D Gudovskikh, R Rybka, I Moloshnikov Procedia Computer Science 66, 307-316, 2015 | 19 | 2015 |
| Modeling the dynamics of spiking networks with memristor-based STDP to solve classification tasks A Sboev, D Vlasov, R Rybka, Y Davydov, A Serenko, V Demin Mathematics 9 (24), 3237, 2021 | 16 | 2021 |
| Morpho-syntactic parsing based on neural networks and corpus data R Rybka, A Sboev, I Moloshnikov, D Gudovskikh 2015 Artificial Intelligence and Natural Language and Information Extraction …, 2015 | 15 | 2015 |
| An algorithm of finding thematically similar documents with creating context-semantic graph based on probabilistic-entropy approach IA Moloshnikov, AG Sboev, RB Rybka, DV Gydovskikh Procedia Computer Science 66, 297-306, 2015 | 14 | 2015 |
| Spiking neural network reinforcement learning method based on temporal coding and STDP A Sboev, D Vlasov, R Rybka, A Serenko Procedia computer science 145, 458-463, 2018 | 12 | 2018 |
| Gender Prediction for Authors of Russian Texts Using Regression And Classification Techniques. T Litvinova, P Seredin, O Litvinova, O Zagorovskaya, A Sboev, ... CDUD@ CLA, 44-53, 2016 | 12 | 2016 |
| An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets A Sboev, S Sboeva, I Moloshnikov, A Gryaznov, R Rybka, A Naumov, ... arXiv preprint arXiv:2105.00059, 2021 | 11 | 2021 |
| Data-driven model for emotion detection in Russian texts A Sboev, A Naumov, R Rybka Procedia Computer Science 190, 637-642, 2021 | 11 | 2021 |
| Analysis of the full-size russian corpus of internet drug reviews with complex ner labeling using deep learning neural networks and language models A Sboev, S Sboeva, I Moloshnikov, A Gryaznov, R Rybka, A Naumov, ... Applied Sciences 12 (1), 491, 2022 | 10 | 2022 |
| Memristor-based spiking neural network with online reinforcement learning D Vlasov, A Minnekhanov, R Rybka, Y Davydov, A Sboev, A Serenko, ... Neural Networks 166, 512-523, 2023 | 9 | 2023 |
| Research of a deep learning neural network effectiveness for a morphological parser of Russian language AG Sboev, DV Gudovskikh, IA Moloshnikov, RB Rybka, I Ivanov, ... Komp'juternaja Lingvistika i Intellektual'nye Tehnologii, 234-244, 2017 | 9 | 2017 |
Иван Молошников, Ivan MoloshnikovНИЦ "Курчатовский институт"在 nrcki.ru 的电子邮件经过验证
