| Interpretable machine learning with an ensemble of gradient boosting machines AV Konstantinov, LV Utkin Knowledge-Based Systems 222, 106993, 2021 | 175 | 2021 |
| A weighted random survival forest LV Utkin, AV Konstantinov, VS Chukanov, MV Kots, MA Ryabinin, ... Knowledge-Based Systems 177, 136-144, 2019 | 53 | 2019 |
| Attention-based random forest and contamination model LV Utkin, AV Konstantinov Neural Networks 154, 346-359, 2022 | 33 | 2022 |
| SurvNAM: The machine learning survival model explanation LV Utkin, ED Satyukov, AV Konstantinov Neural Networks 147, 81-102, 2022 | 32 | 2022 |
| Counterfactual explanation of machine learning survival models M Kovalev, L Utkin, F Coolen, A Konstantinov Informatica 32 (4), 817-847, 2021 | 25 | 2021 |
| Ensembles of random SHAPs L Utkin, A Konstantinov Algorithms 15 (11), 431, 2022 | 22 | 2022 |
| A deep forest improvement by using weighted schemes L Utkin, A Konstantinov, A Meldo, M Ryabinin, V Chukanov 2019 24th Conference of Open Innovations Association (FRUCT), 451-456, 2019 | 16 | 2019 |
| Deep Forest as a framework for a new class of machine-learning models LV Utkin, AA Meldo, AV Konstantinov National Science Review 6 (2), 186-187, 2019 | 16 | 2019 |
| Gradient Boosting Machine with Partially Randomized Decision Trees A Konstantinov, L Utkin, V Muliukha 2021 28th Conference of Open Innovations Association (FRUCT), 2021 | 15 | 2021 |
| A new adaptive weighted deep forest and its modifications LV Utkin, AV Konstantinov, VS Chukanov, AA Meldo International Journal of Information Technology & Decision Making 19 (04 …, 2020 | 15 | 2020 |
| Multi-attention multiple instance learning AV Konstantinov, LV Utkin Neural Computing and Applications 34 (16), 14029-14051, 2022 | 14 | 2022 |
| A new computationally simple approach for implementing neural networks with output hard constraints AV Konstantinov, LV Utkin Doklady Mathematics 108 (Suppl 2), S233-S241, 2023 | 11 | 2023 |
| A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines ULV Konstantinov A.V. Studies in Systems, Decision and Control 350, 3–16, 2021 | 9 | 2021 |
| Combining an autoencoder and a variational autoencoder for explaining the machine learning model predictions L Utkin, P Drobintsev, M Kovalev, A Konstantinov 2021 28th Conference of Open Innovations Association (FRUCT), 489-494, 2021 | 8 | 2021 |
| Neural Attention Forests: Transformer-Based Forest Improvement AV Konstantinov, LV Utkin, AA Lukashin, VA Muliukha Proceedings of the Seventh International Scientific Conference “Intelligent …, 2023 | 7 | 2023 |
| Improved Anomaly detection by using the attention-based isolation forest L Utkin, A Ageev, A Konstantinov, V Muliukha Algorithms 16 (1), 19, 2022 | 7 | 2022 |
| AGBoost: Attention-based modification of gradient boosting machine A Konstantinov, L Utkin, S Kirpichenko 2022 31st Conference of Open Innovations Association (FRUCT), 96-101, 2022 | 7 | 2022 |
| Attention and self-attention in random forests LV Utkin, AV Konstantinov, SR Kirpichenko Progress in Artificial Intelligence 12 (3), 257-273, 2023 | 5 | 2023 |
| Attention-like feature explanation for tabular data AV Konstantinov, LV Utkin International Journal of Data Science and Analytics 16 (1), 1-26, 2023 | 5 | 2023 |
| An extension of the neural additive model for uncertainty explanation of machine learning survival models L Utkin, A Konstantinov Cyber-Physical Systems: Intelligent Models and Algorithms, 3-13, 2022 | 5 | 2022 |
