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Publications in Math-Net.Ru
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FoCAT: foundation model for estimating the conditional average treatment effect
Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025), 182–191
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Improved anomaly detection by using the attention-based isolation forest with trainable scoring function
Computing, Telecommunication and Control, 18:1 (2025), 7–22
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Ada-naf: semi-supervised anomaly detection based on the neural attention forest
Informatics and Automation, 24:1 (2025), 329–357
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Generating survival interpretable trajectories and data
Dokl. RAN. Math. Inf. Proc. Upr., 520:2 (2024), 85–97
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A new computationally simple approach for implementing neural networks with output hard constraints
Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 80–90
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Flexible deep forest classifier with multi-head attention
Computing, Telecommunication and Control, 16:2 (2023), 7–16
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Random survival forests incorporated by the Nadaraya-Watson regression
Informatics and Automation, 21:5 (2022), 851–880
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Deep gradient boosting for regression problems
Computing, Telecommunication and Control, 14:3 (2021), 7–19
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Predictive models and dynamics of estimates of applied tasks characteristics using machine learning methods
Computing, Telecommunication and Control, 17:3 (2024), 54–60
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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
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