| SurvLIME: A method for explaining machine learning survival models MS Kovalev, LV Utkin, EM Kasimov Knowledge-Based Systems 203, 106164, 2020 | 98 | 2020 |
| A deep forest classifier with weights of class probability distribution subsets LV Utkin, MS Kovalev, AA Meldo Knowledge-Based Systems 173, 15-27, 2019 | 58 | 2019 |
| The natural language explanation algorithms for the lung cancer computer-aided diagnosis system A Meldo, L Utkin, M Kovalev, E Kasimov Artificial intelligence in medicine 108, 101952, 2020 | 49 | 2020 |
| A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov–Smirnov bounds MS Kovalev, LV Utkin Neural Networks 132, 1-18, 2020 | 43 | 2020 |
| Imprecise weighted extensions of random forests for classification and regression LV Utkin, MS Kovalev, FPA Coolen Applied Soft Computing 92, 106324, 2020 | 31 | 2020 |
| An explanation method for siamese neural networks L Utkin, M Kovalev, E Kasimov Proceedings of International Scientific Conference on Telecommunications …, 2021 | 27 | 2021 |
| Counterfactual explanation of machine learning survival models M Kovalev, L Utkin, F Coolen, A Konstantinov Informatica 32 (4), 817-847, 2021 | 26 | 2021 |
| An ensemble of triplet neural networks for differential diagnostics of lung cancer L Utkin, A Meldo, M Kovalev, E Kasimov 2019 25th Conference of Open Innovations Association (FRUCT), 346-352, 2019 | 14 | 2019 |
| Survlime-inf: A simplified modification of survlime for explanation of machine learning survival models LV Utkin, MS Kovalev, EM Kasimov arXiv preprint arXiv:2005.02387, 2020 | 13 | 2020 |
| A pipeline for classifying deleterious coding mutations in agricultural plants MS Kovalev, AA Igolkina, MG Samsonova, SV Nuzhdin Frontiers in plant science 9, 1734, 2018 | 13 | 2018 |
| 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 | 9 | 2021 |
| A review of methods for explaining and interpreting decisions of intelligent cancer diagnosis systems LV Utkin, AA Meldo, MS Kovalev, EM Kasimov Scientific and Technical Information Processing 48 (5), 398-405, 2021 | 7 | 2021 |
| Imprecise extensions of random forests and random survival forests L Utkin, M Kovalev, A Meldo, F Coolen International Symposium on Imprecise Probabilities: Theories and …, 2019 | 7 | 2019 |
| Uncertainty interpretation of the machine learning survival model predictions LV Utkin, VS Zaborovsky, MS Kovalev, AV Konstantinov, NA Politaeva, ... IEEE Access 9, 120158-120175, 2021 | 5 | 2021 |
| An explanation method for black-box machine learning survival models using the Chebyshev distance LV Utkin, MS Kovalev, EM Kasimov Conference on Artificial Intelligence and Natural Language, 62-74, 2020 | 5 | 2020 |
| A simple general algorithm for the diagnosis explanation of computer-aided diagnosis systems in terms of natural language primitives LV Utkin, AA Meldo, MS Kovalev, EM Kasimov 2020 XXIII International Conference on Soft Computing and Measurements (SCM …, 2020 | 4 | 2020 |
| Explanation of siamese neural networks for weakly supervised learning L Utkin, M Kovalev, E Kasimov Computing and Informatics 39 (6), 1172–1202-1172–1202, 2020 | 4 | 2020 |
| Robust regression random forests by small and noisy training data LV Utkin, MS Kovalev, PAF Coolen 2019 XXII International Conference on Soft Computing and Measurements (SCM …, 2019 | 4 | 2019 |
| Heat stress analysis suggests a genetic basis for tolerance in Macrocystis pyrifera across developmental stages M Harden, M Kovalev, G Molano, C Yorke, R Miller, D Reed, F Alberto, ... Communications Biology 7 (1), 1147, 2024 | 2 | 2024 |
| Metagenome-assembled genomes from photo-oxidized and nonoxidized oil-degrading marine microcosms SJ Barnes, RC Althouse, BF Costa, B Hu, M Kovalev, T Kulik, YT Lee, ... Microbiology Resource Announcements 12 (6), e00210-23, 2023 | 2 | 2023 |
