Utkin Lev Vladimirovich

Publications in Math-Net.Ru

1. FoCAT: foundation model for estimating the conditional average treatment effect
   
   Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025),  182–191
2. Improved anomaly detection by using the attention-based isolation forest with trainable scoring function
   
   Computing, Telecommunication and Control, 18:1 (2025),  7–22
3. Ada-naf: semi-supervised anomaly detection based on the neural attention forest
   
   Informatics and Automation, 24:1 (2025),  329–357
4. Generating survival interpretable trajectories and data
   
   Dokl. RAN. Math. Inf. Proc. Upr., 520:2 (2024),  85–97
5. A model for explainable malignancy assessment of pulmonary nodules on CT images
   
   Artificial Intelligence and Decision Making, 2024, no. 4,  123–134
6. A new computationally simple approach for implementing neural networks with output hard constraints
   
   Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023),  80–90
7. Flexible deep forest classifier with multi-head attention
   
   Computing, Telecommunication and Control, 16:2 (2023),  7–16
8. Random survival forests incorporated by the Nadaraya-Watson regression
   
   Informatics and Automation, 21:5 (2022),  851–880
9. A review of methods for explaining and interpreting decisions of intelligent cancer diagnosis systems
   
   Artificial Intelligence and Decision Making, 2020, no. 4,  55–65
10. Robust algorithms of data classification obtained using set of weights by group of robots
    
    St. Petersburg Polytechnical University Journal. Computer Science. Telecommunication and Control Sys, 12:1 (2019),  44–54
11. A review of the intelligent lung cancer diagnosis methods
    
    Artificial Intelligence and Decision Making, 2018, no. 3,  28–38
12. A high-performance genome-wide association study algorithm based on analysis of pairs of individuals
    
    Tr. SPIIRAN, 58 (2018),  5–26
13. Reliability of repairable reserved systems with failure aftereffect
    
    Avtomat. i Telemekh., 2017, no. 1,  137–151
14. A Genome-Wide Association Study using Pairwise Comparison Matrices
    
    Tr. SPIIRAN, 47 (2016),  225–240
15. A classification model on the basis of partial information about features in the form of their mean values
    
    Artificial Intelligence and Decision Making, 2012, no. 3,  71–81
16. A classification model on the basis of partial information about features in the form of their mean values
    
    Artificial Intelligence and Decision Making, 2012, no. 2,  16–26
17. New interval bayesian software reliability models on the basis of the non-homogeneous Poisson processes
    
    Probl. Upr., 2009, no. 6,  52–58


18. Interpretation methods for machine learning models in the framework of survival analysis with censored data: a brief overview
    
    Computing, Telecommunication and Control, 17:3 (2024),  22–31
19. Exo-intelligent hybrid supercomputer platforms for shared-use centers
    
    Computing, Telecommunication and Control, 17:3 (2024),  9–21
20. Рудаков Константин Владимирович (21.06.1954 – 10.07.2021). Памяти академика информатики
    
    Vestnik YuUrGU. Ser. Mat. Model. Progr., 15:1 (2022),  128–130
21. Vladimir Evgenievich Pavlovsky (22.05.1950–03.06.2020)
    
    Vestnik YuUrGU. Ser. Mat. Model. Progr., 13:3 (2020),  116–118