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Publications
Orcid ID
0000-0002-8910-4775
Machine learning models to determine unobservable centrality-related parameter values for a wide range of nuclear systems at the energy of 200 GeV
- Year: 2023
- Volume: 16
- Issue: 2
- 94
- 4742
- Pages: 111-120
Machine learning models to find unobservable centrality-related parameter values in collisions of different nuclei in the initial energy range from 40 to 200 GeV
- Year: 2023
- Volume: 16
- Issue: 2
- 47
- 4413
- Pages: 121-131
A generator of deep inelastic lepton-proton scattering based on the Generative-Adversarial Network (GAN)
- Year: 2023
- Volume: 16
- Issue: 4
- 60
- 3767
- Pages: 181-188
Simulation of semi-inclusive deep inelastic lepton scattering on a proton at energies of 20 — 100 GeV on the basis of the Generative-Adversarial Neural Network
- Year: 2023
- Volume: 16
- Issue: 4
- 46
- 3675
- Pages: 189-197
A generative adversarial network as the basis for a semi-inclusive deep inelastic lepton scattering generator on a polarized proton
- Year: 2024
- Volume: 17
- Issue: 1
- 87
- 3425
- Pages: 93-102
Direct photon asymmetries in the longitudinally polarized proton-proton collisions at an energy of 27 GeV
- Year: 2025
- Volume: 18
- Issue: 1
- 39
- 3633
- Pages: 142-148
Direct photon asymmetries in the longitudinally polarized proton-proton collisions at energies from 9 to 27 GeV
- Year: 2025
- Volume: 18
- Issue: 3
- 24
- 2031
- Pages: 91-97