15 citations to https://www.mathnet.ru/rus/math5
  1. Szilárd Molnár, Levente Tamás, “Variational autoencoders for 3D data processing”, Artif Intell Rev, 57:2 (2024)  crossref
  2. Ian Grooms, Christopher Riedel, “A Quantile-Conserving Ensemble Filter Based on Kernel-Density Estimation”, Remote Sensing, 16:13 (2024), 2377  crossref
  3. Aleksandr Sergeev, Elena Baglaeva, Andrey Shichkin, Alexander Buevich, “The statistical analysis of training data representativeness for artificial neural networks: spatial distribution modelling of heavy metals in topsoil”, Earth Sci Inform, 2024  crossref
  4. Pedro Fernandes, Séamus Ó Ciardhuáin, Mário Antunes, “Unveiling Malicious Network Flows Using Benford's Law”, Mathematics, 12:15 (2024), 2299  crossref
  5. C. M. Salooja, Arjun Sanker, K. Deepthi, A. S. Jereesh, “An ensemble approach for circular RNA-disease association prediction using variational autoencoder and genetic algorithm”, J. Bioinform. Comput. Biol., 22:04 (2024)  crossref
  6. Nir Y. Krakauer, “Extending the blended generalized extreme value distribution”, Discov Civ Eng, 1:1 (2024)  crossref
  7. Vladimir Glinskiy, Artem Logachov, Olga Logachova, Helder Rojas, Lyudmila Serga, Anatoly Yambartsev, “Asymptotic Properties of a Statistical Estimator of the Jeffreys Divergence: The Case of Discrete Distributions”, Mathematics, 12:21 (2024), 3319  crossref
  8. Zahra Ghorbanali, Fatemeh Zare-Mirakabad, Najmeh Salehi, Mohammad Akbari, Ali Masoudi-Nejad, “DrugRep-HeSiaGraph: when heterogenous siamese neural network meets knowledge graphs for drug repurposing”, BMC Bioinformatics, 24:1 (2023)  crossref
  9. 许康 Xu Kang, 祝永新 Zhu Yongxin, 吴波 Wu Bo, 郑小盈 Zheng Xiaoying, 陈凌曜 Chen Lingyao, “基于隐私保护机制的辐射光源衍射图像筛选”, Laser Optoelectron. Prog., 60:10 (2023), 1010020  crossref
  10. “Тезисы докладов, представленных на Седьмой международной конференции по стохастическим методам. I”, Теория вероятн. и ее примен., 67:4 (2022), 819–836  mathnet  crossref; “Abstracts of talks given at the 7th International Conference on Stochastic Methods, I”, Theory Probab. Appl., 67:4 (2022), 652–652  crossref
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