Speciality:
05.13.18 (Mathematical modelling, calculating methods, and the program systems)
E-mail: Keywords: semiparametric statistical methods, probability and statistical models, mixture distributions, computational statistics methods, data analysis, machine learning, neural networks
Subject:
Development and analytical study of semiparametric methods for constructing and analyzing probabilistic-statistical models of heterogeneous data, focused on the situation of lack or absence of a priori information about the physical nature of the processes under study. Development of statistical approaches to improve the accuracy of machine learning methods.
Main publications:
Gorshenin A. K., “Adaptive detection of normal mixture signals with pre-estimated Gaussian mixture noise”, Pattern Recognition and Image Analysis, 29:3 (2019), 377-383
Gorshenin A. K., Korolev V. Yu., Zeifman A. I., “Modeling particle size distribution in lunar regolith via a central limit theorem for random sums”, Mathematics, 8:9 (2020), 1409
Gorshenin A. K., Kuzmin V. Yu., “Improved architecture and configurations
of feedforward neural networks to increase accuracy of predictions for moments of
finite normal mixtures”, Pattern Recognition and Image Analysis, 29:1 (2019), 79-88
Korolev V. Yu., Gorshenin A. K., “Probability models and statistical tests for extreme precipitation based on generalized negative binomial distributions”, Mathematics, 8:4 (2020), 604
Batanov G. M., Borzosekov V. D., Gorshenin A. K., Kharchev N. K., Korolev V. Yu., Sarskyan K. A., “Evolution of statistical properties
of microturbulence during transient process under electron cyclotron resonance
heating of the L-2M stellarator plasma”, Plasma Physics and Controlled Fusion, 61:7 (2019), 075006
ISTINA
