Lev V. Utkin - RankMe

149 papers B 1Misc 7Journal 127Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Regression Analysis Under Interval-Valued Targets as an Imprecise Classification Problem. Algorithms Lev V. Utkin, Stanislav Kogan, Andrei V. Konstantinov, Vladimir Muliukha
2025	J	`jnl`	A novel gradient-based method for decision trees optimizing arbitrary differential loss functions. CoRR Andrei V. Konstantinov, Lev V. Utkin
2025	J	`jnl`	Automated Video-EEG Analysis in Epilepsy Studies: A Narrative Review of Advances and Challenges. J. Medical Syst. Valerii A. Zuev, Elena G. Salmagambetova, Stepan N. Djakov, Lev V. Utkin
2025	J	`jnl`	Automated Video-EEG Analysis in Epilepsy Studies: Advances and Challenges. CoRR Valerii A. Zuev, Elena G. Salmagambetova, Stepan N. Djakov, Lev V. Utkin
2025	J	`jnl`	Dual feature-based and example-based explanation methods. Frontiers Artif. Intell. Andrei V. Konstantinov, Boris V. Kozlov, Stanislav Kirpichenko, Lev V. Utkin, Vladimir Muliukha
2025	J	`jnl`	Ensemble-Based Survival Models with the Self-Attended Beran Estimator Predictions. CoRR Lev V. Utkin, Semen P. Khomets, Vlada A. Efremenko, Andrei V. Konstantinov, Natalya M. Verbova
2025	—	`conf`	Set-Input Trees: An Interpretable Multiple Instance Learning Architecture for Robotics. ICR (2) Andrei V. Konstantinov, Lev V. Utkin
2025	J	`jnl`	SurvBeNIM: The Beran-Based Neural Importance Model for Explaining Survival Models. IEEE Access Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov, Vladimir Mulukha
2025	J	`jnl`	SurvBeX: an explanation method of the machine learning survival models based on the Beran estimator. Int. J. Data Sci. Anal. Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
2025	J	`jnl`	Survival Analysis as Imprecise Classification with Trainable Kernels. CoRR Andrei V. Konstantinov, Vlada A. Efremenko, Lev V. Utkin
2025	J	`jnl`	Survival Concept-Based Learning Models. CoRR Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov, Natalya M. Verbova
2025	J	`jnl`	Survival concept-based learning models. J. Intell. Inf. Syst. Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov, Natalya M. Verbova
2025	J	`jnl`	Towards a Relationship-Aware Transformer for Tabular Data. CoRR Andrei V. Konstantinov, Valerii A. Zuev, Lev V. Utkin
2024	J	`jnl`	BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect. Algorithms Stanislav Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov, Vladimir Muliukha
2024	J	`jnl`	Concept-based Explainable Malignancy Scoring on Pulmonary Nodules in CT Images. CoRR Rinat I. Dumaev, Sergei A. Molodyakov, Lev V. Utkin
2024	J	`jnl`	Dual feature-based and example-based explanation methods. CoRR Andrei V. Konstantinov, Boris V. Kozlov, Stanislav R. Kirpichenko, Lev V. Utkin
2024	J	`jnl`	FI-CBL: A Probabilistic Method for Concept-Based Learning with Expert Rules. CoRR Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko
2024	J	`jnl`	Generating Survival Interpretable Trajectories and Data. CoRR Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin
2024	J	`jnl`	Incorporating Expert Rules into Neural Networks in the Framework of Concept-Based Learning. CoRR Andrei V. Konstantinov, Lev V. Utkin
2024	J	`jnl`	SurvBETA: Ensemble-Based Survival Models Using Beran Estimators and Several Attention Mechanisms. CoRR Lev V. Utkin, Semen P. Khomets, Vlada A. Efremenko, Andrei V. Konstantinov
2023	J	`jnl`	A New Computationally Simple Approach for Implementing Neural Networks with Output Hard Constraints. CoRR Andrei V. Konstantinov, Lev V. Utkin
2023	J	`jnl`	Attention and self-attention in random forests. Prog. Artif. Intell. Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko
2023	J	`jnl`	Attention-like feature explanation for tabular data. Int. J. Data Sci. Anal. Andrei V. Konstantinov, Lev V. Utkin
2023	—	`conf`	GBMILs: Gradient Boosting Models for Multiple Instance Learning. ICR Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha, Vladimir S. Zaborovsky
2023	J	`jnl`	Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. Algorithms Andrei V. Konstantinov, Stanislav Kirpichenko, Lev V. Utkin
2023	J	`jnl`	Improved Anomaly Detection by Using the Attention-Based Isolation Forest. Algorithms Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov, Vladimir Muliukha
2023	J	`jnl`	Interpretable Ensembles of Hyper-Rectangles as Base Models. CoRR Andrei V. Konstantinov, Lev V. Utkin
2023	J	`jnl`	Interpretable ensembles of hyper-rectangles as base models. Neural Comput. Appl. Andrei V. Konstantinov, Lev V. Utkin
2023	J	`jnl`	LARF: Two-Level Attention-Based Random Forests with a Mixture of Contamination Models. Informatics Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
2023	J	`jnl`	Multiple Instance Learning with Trainable Decision Tree Ensembles. CoRR Andrei V. Konstantinov, Lev V. Utkin
2023	J	`jnl`	Multiple Instance Learning with Trainable Soft Decision Tree Ensembles. Algorithms Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
2023	J	`jnl`	Neural Attention Forests: Transformer-Based Forest Improvement. CoRR Andrei V. Konstantinov, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha
2023	J	`jnl`	SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models. CoRR Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
2023	J	`jnl`	SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator. CoRR Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
2022	Misc	`conf`	AGBoost: Attention-based Modification of Gradient Boosting Machine. FRUCT Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko
2022	J	`jnl`	AGBoost: Attention-based Modification of Gradient Boosting Machine. CoRR Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko
2022	J	`jnl`	Attention and Self-Attention in Random Forests. CoRR Lev V. Utkin, Andrei V. Konstantinov
2022	J	`jnl`	Attention-based Random Forest and Contamination Model. CoRR Lev V. Utkin, Andrei V. Konstantinov
2022	J	`jnl`	Attention-based random forest and contamination model. Neural Networks Lev V. Utkin, Andrei V. Konstantinov
2022	J	`jnl`	BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect. CoRR Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov
2022	J	`jnl`	Ensembles of Random SHAPs. Algorithms Lev V. Utkin, Andrei V. Konstantinov
2022	J	`jnl`	Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. CoRR Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin
2022	J	`jnl`	Improved Anomaly Detection by Using the Attention-Based Isolation Forest. CoRR Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov
2022	J	`jnl`	LARF: Two-level Attention-based Random Forests with a Mixture of Contamination Models. CoRR Andrei V. Konstantinov, Lev V. Utkin
2022	J	`jnl`	Multi-attention multiple instance learning. Neural Comput. Appl. Andrei V. Konstantinov, Lev V. Utkin
2022	Misc	`conf`	Multiple Instance Learning through Explanation by Using a Histopathology Example. FRUCT Andrei V. Konstantinov, Lev V. Utkin
2022	J	`jnl`	SurvNAM: The machine learning survival model explanation. Neural Networks Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov
2021	J	`jnl`	An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data. CoRR Lev V. Utkin, Andrei V. Konstantinov, Kirill A. Vishniakov
2021	J	`jnl`	Attention-like feature explanation for tabular data. CoRR Andrei V. Konstantinov, Lev V. Utkin
2021	Misc	`conf`	Combining an Autoencoder and a Variational Autoencoder for Explaining the Machine Learning Model Predictions. FRUCT Lev V. Utkin, Pavel D. Drobintsev, Maxim Kovalev, Andrei V. Konstantinov
2021	J	`jnl`	Counterfactual Explanation of Machine Learning Survival Models. Informatica Maxim Kovalev, Lev V. Utkin, Frank P. A. Coolen, Andrei V. Konstantinov
2021	J	`jnl`	Ensembles of Random SHAPs. CoRR Lev V. Utkin, Andrei V. Konstantinov
2021	Misc	`conf`	Gradient Boosting Machine with Partially Randomized Decision Trees. FRUCT Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
2021	J	`jnl`	Interpretable machine learning with an ensemble of gradient boosting machines. Knowl. Based Syst. Andrei V. Konstantinov, Lev V. Utkin
2021	J	`jnl`	Multi-Attention Multiple Instance Learning. CoRR Andrei V. Konstantinov, Lev V. Utkin
2021	J	`jnl`	SurvNAM: The machine learning survival model explanation. CoRR Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov
2021	J	`jnl`	Uncertainty Interpretation of the Machine Learning Survival Model Predictions. IEEE Access Lev V. Utkin, Vladimir S. Zaborovsky, Maxim S. Kovalev, Andrei V. Konstantinov, Natalia A. Politaeva, Alexey Lukashin
2020	J	`jnl`	A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines. CoRR Andrei V. Konstantinov, Lev V. Utkin
2020	J	`jnl`	A New Adaptive Weighted Deep Forest and Its Modifications. Int. J. Inf. Technol. Decis. Mak. Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Anna A. Meldo
2020	J	`jnl`	A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds. CoRR Maxim S. Kovalev, Lev V. Utkin
2020	J	`jnl`	A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds. Neural Networks Maxim S. Kovalev, Lev V. Utkin
2020	J	`jnl`	An imprecise deep forest for classification. Expert Syst. Appl. Lev V. Utkin
2020	B	`conf`	Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System. ESANN Vladimir Muliukha, Alexey Lukashin, Lev V. Utkin, Mikhail Popov, Anna A. Meldo
2020	J	`jnl`	Counterfactual explanation of machine learning survival models. CoRR Maxim S. Kovalev, Lev V. Utkin
2020	J	`jnl`	Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors. Int. J. Artif. Intell. Tools Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov, Andrei V. Konstantinov, Anna A. Meldo
2020	J	`jnl`	Explanation of Siamese Neural Networks for Weakly Supervised Learning. Comput. Informatics Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov
2020	J	`jnl`	Gradient boosting machine with partially randomized decision trees. CoRR Andrei V. Konstantinov, Lev V. Utkin
2020	J	`jnl`	Imprecise weighted extensions of random forests for classification and regression. Appl. Soft Comput. Lev V. Utkin, Maxim S. Kovalev, Frank P. A. Coolen
2020	J	`jnl`	Improvement of the Deep Forest Classifier by a Set of Neural Networks. Informatica (Slovenia) Lev V. Utkin, Kirill D. Zhuk
2020	J	`jnl`	Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines. CoRR Andrei V. Konstantinov, Lev V. Utkin
2020	J	`jnl`	SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models. CoRR Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov
2020	J	`jnl`	SurvLIME: A method for explaining machine learning survival models. CoRR Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov
2020	J	`jnl`	SurvLIME: A method for explaining machine learning survival models. Knowl. Based Syst. Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov
2020	J	`jnl`	The natural language explanation algorithms for the lung cancer computer-aided diagnosis system. Artif. Intell. Medicine Anna A. Meldo, Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov
2019	Misc	`conf`	A Deep Forest Improvement by Using Weighted Schemes. FRUCT Lev V. Utkin, Andrei V. Konstantinov, Anna A. Meldo, Mikhail A. Ryabinin, Viacheslav S. Chukanov
2019	J	`jnl`	A deep forest classifier with weights of class probability distribution subsets. Knowl. Based Syst. Lev V. Utkin, Maxim Kovalev, Anna A. Meldo
2019	J	`jnl`	A weighted random survival forest. CoRR Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo
2019	J	`jnl`	A weighted random survival forest. Knowl. Based Syst. Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo
2019	J	`jnl`	An Adaptive Weighted Deep Forest Classifier. CoRR Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Anna A. Meldo
2019	Misc	`conf`	An Ensemble of Triplet Neural Networks for Differential Diagnostics of Lung Cancer. FRUCT Lev V. Utkin, Anna A. Meldo, Maxim Kovalev, Ernest M. Kasimov
2019	J	`jnl`	An explanation method for Siamese neural networks. CoRR Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov
2019	J	`jnl`	An imprecise extension of SVM-based machine learning models. Neurocomputing Lev V. Utkin
2019	Misc	`conf`	Database Acquisition for the Lung Cancer Computer Aided Diagnostic Systems. FRUCT Anna A. Meldo, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha, Vladimir S. Zaborovsky
2019	J	`jnl`	Discriminative Metric Learning with Deep Forest. Int. J. Artif. Intell. Tools Lev V. Utkin, Mikhail A. Ryabinin
2019	J	`jnl`	Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors. CoRR Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov
2019	—	`conf`	Imprecise Extensions of Random Forests and Random Survival Forests. ISIPTA Lev V. Utkin, Maxim Kovalev, Anna A. Meldo, Frank P. A. Coolen
2018	J	`jnl`	A Siamese Deep Forest. Knowl. Based Syst. Lev V. Utkin, Mikhail A. Ryabinin
2018	J	`jnl`	A modification of the Lasso method by using the Bahadur representation for the genome-wide association study. Informatica (Slovenia) Lev V. Utkin, Yulia A. Zhuk
2018	J	`jnl`	A robust weighted SVR-based software reliability growth model. Reliab. Eng. Syst. Saf. Lev V. Utkin, Frank P. A. Coolen
2017	J	`jnl`	A Siamese Deep Forest. CoRR Lev V. Utkin, Mikhail A. Ryabinin
2017	J	`jnl`	An one-class classification support vector machine model by interval-valued training data. Knowl. Based Syst. Lev V. Utkin, Yulia A. Zhuk
2017	J	`jnl`	Discriminative Metric Learning with Deep Forest. CoRR Lev V. Utkin, Mikhail A. Ryabinin
2017	J	`jnl`	Interval SVM-Based Classification Algorithm Using the Uncertainty Trick. Int. J. Artif. Intell. Tools Lev V. Utkin, Yulia A. Zhuk
2017	J	`jnl`	Reliability of repairable reserved systems with failure aftereffect. Autom. Remote. Control. Sergey V. Gurov, Lev V. Utkin
2017	J	`jnl`	Siamese neural network for intelligent information security control in multi-robot systems. Autom. Control. Comput. Sci. Lev V. Utkin, Vladimir S. Zaborovsky, Sergey G. Popov
2016	J	`jnl`	Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels. Neural Networks Lev V. Utkin, Anatoly I. Chekh, Yulia A. Zhuk
2016	J	`jnl`	Detection of anomalous behavior in a robot system based on deep learning elements. Autom. Control. Comput. Sci. Lev V. Utkin, V. S. Zaborovskii, Sergey G. Popov
2015	J	`jnl`	A new robust model of one-class classification by interval-valued training data using the triangular kernel. Neural Networks Lev V. Utkin, Anatoly I. Chekh
2015	J	`jnl`	Imprecise inference for warranty contract analysis. Reliab. Eng. Syst. Saf. Lev V. Utkin, Frank P. A. Coolen, Sergey V. Gurov
2015	J	`jnl`	Improving over-fitting in ensemble regression by imprecise probabilities. Inf. Sci. Lev V. Utkin, Andrea Wiencierz
2015	J	`jnl`	Robust Classifiers Using Imprecise Probability Models and Importance of Classes. Int. J. Artif. Intell. Tools Lev V. Utkin, Yulia A. Zhuk
2015	J	`jnl`	The imprecise Dirichlet model as a basis for a new boosting classification algorithm. Neurocomputing Lev V. Utkin
2014	—	`conf`	A Robust One-Class Classification Model with Interval-Valued Data Based on Belief Functions and Minimax Strategy. MLDM Lev V. Utkin, Yulia A. Zhuk, Anatoly I. Chekh
2014	J	`jnl`	A framework for imprecise robust one-class classification models. Int. J. Mach. Learn. Cybern. Lev V. Utkin
2014	J	`jnl`	Imprecise prior knowledge incorporating into one-class classification. Knowl. Inf. Syst. Lev V. Utkin, Yulia A. Zhuk
2014	J	`jnl`	Robust boosting classification models with local sets of probability distributions. Knowl. Based Syst. Lev V. Utkin, Yulia A. Zhuk
2013	J	`jnl`	An Imprecise Boosting-like Approach to Classification. Int. J. Pattern Recognit. Artif. Intell. Lev V. Utkin
2013	J	`jnl`	Fuzzy decision making using the imprecise Dirichlet model. Int. J. Math. Oper. Res. Lev V. Utkin, Yulia A. Zhuk
2013	J	`jnl`	Imprecise Imputation as a Tool for Solving Classification Problems with Mean Values of Unobserved Features. Adv. Artif. Intell. Lev V. Utkin, Yulia A. Zhuk
2013	J	`jnl`	Robust novelty detection in the framework of a contamination neighbourhood. Int. J. Intell. Inf. Database Syst. Lev V. Utkin, Yulia A. Zhuk
2012	—	`conf`	A Pessimistic Approach for Solving a Multi-criteria Decision Making. KSE Van Hieu Nguyen, Lev V. Utkin, Dang Duy Thang
2012	J	`jnl`	A machine learning algorithm for classification under extremely scarce information. Int. J. Data Anal. Tech. Strateg. Lev V. Utkin, Yulia A. Zhuk
2012	J	`jnl`	Combining of judgments in imprecise voting multi-criteria decision problems. Int. J. Appl. Decis. Sci. Lev V. Utkin, Yulia A. Zhuk
2012	J	`jnl`	Fuzzy One-Class Classification Model Using Contamination Neighborhoods. Adv. Fuzzy Syst. Lev V. Utkin
2012	J	`jnl`	The DS/AHP Method under Partial Information about Criteria and Alternatives by Several Levels of Criteria. Int. J. Inf. Technol. Decis. Mak. Lev V. Utkin, Natalia V. Simanova
2011	—	`ch.`	Imprecise Reliability. International Encyclopedia of Statistical Science Frank P. A. Coolen, Lev V. Utkin
2010	J	`jnl`	Regression analysis using the imprecise Bayesian normal model. Int. J. Data Anal. Tech. Strateg. Lev V. Utkin
2009	J	`jnl`	A new ranking procedure by incomplete pairwise comparisons using preference subsets. Intell. Data Anal. Lev V. Utkin
2009	J	`jnl`	Computing expectations with continuous p-boxes: Univariate case. Int. J. Approx. Reason. Lev V. Utkin, Sébastien Destercke
2007	J	`jnl`	Decision making under incomplete data using the imprecise Dirichlet model. Int. J. Approx. Reason. Lev V. Utkin, Thomas Augustin
2007	—	`ch.`	Imprecise reliability: An introductory overview. Intelligence in Reliability Engineering Lev V. Utkin, Frank P. A. Coolen
2007	J	`jnl`	Risk Analysis under Partial Prior Information and Nonmonotone Utility Functions. Int. J. Inf. Technol. Decis. Mak. Lev V. Utkin
2007	J	`jnl`	Second-order uncertainty calculations by using the imprecise Dirichlet model. Intell. Data Anal. Lev V. Utkin
2006	J	`jnl`	A method for processing the unreliable expert judgments about parameters of probability distributions. Eur. J. Oper. Res. Lev V. Utkin
2006	J	`jnl`	Cautious Analysis of Project Risks by Interval-Valued Initial Data. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Lev V. Utkin
2006	J	`jnl`	Ranking procedures by pairwise comparison using random sets and the imprecise Dirichlet model. Appl. Math. Comput. Lev V. Utkin
2005	J	`jnl`	Comments on the paper "A behavioural model for vague probability assessments" by Gert de Cooman. Fuzzy Sets Syst. Lev V. Utkin
2005	J	`jnl`	Computing System Reliability Given Interval-Valued Characteristics of the Components. Reliab. Comput. Lev V. Utkin, Igor Kozine
2005	J	`jnl`	Constructing imprecise probability distributions. Int. J. Gen. Syst. Igor Kozine, Lev V. Utkin
2005	—	`conf`	Decision making under incomplete data using the imprecise Dirichlet model. ISIPTA Lev V. Utkin, Thomas Augustin
2005	J	`jnl`	Extensions of belief functions and possibility distributions by using the imprecise Dirichlet model. Fuzzy Sets Syst. Lev V. Utkin
2005	J	`jnl`	Imprecise second-order model for a system of independent random variables. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Lev V. Utkin
2005	—	`conf`	Powerful algorithms for decision making under partial prior information and general ambiguity attitudes. ISIPTA Lev V. Utkin, Thomas Augustin
2004	J	`jnl`	A new efficient algorithm for computing the imprecise reliability of monotone systems. Reliab. Eng. Syst. Saf. Lev V. Utkin
2004	J	`jnl`	An approach to combining unreliable pieces of evidence and their propagation in a system response analysis. Reliab. Eng. Syst. Saf. Igor Kozine, Lev V. Utkin
2004	J	`jnl`	Interval reliability of typical systems with partially known probabilities. Eur. J. Oper. Res. Lev V. Utkin
2004	J	`jnl`	Reliability models of Comput. Oper. Res. Lev V. Utkin
2003	—	`conf`	A Second-Order Uncertainty Model of Independent Random Variables: An Example of the Stress-Strength Reliability. ISIPTA Lev V. Utkin
2003	J	`jnl`	A second-order uncertainty model for calculation of the interval system reliability. Reliab. Eng. Syst. Saf. Lev V. Utkin
2003	—	`conf`	Decision Making with Imprecise Second-Order Probabilities. ISIPTA Lev V. Utkin
2003	J	`jnl`	Imprecise Second-Order Hierarchical Uncertainty Model . Int. J. Uncertain. Fuzziness Knowl. Based Syst. Lev V. Utkin
2002	J	`jnl`	Interval-Valued Finite Markov Chains. Reliab. Comput. Igor Kozine, Lev V. Utkin
2002	J	`jnl`	Stress-strength reliability models under incomplete information. Int. J. Gen. Syst. Lev V. Utkin, Igor Kozine
2001	—	`conf`	Computing the reliability of complex systems. ISIPTA Igor Kozine, Lev V. Utkin
2001	—	`conf`	Different faces of the natural extension. ISIPTA Igor Kozine, Lev V. Utkin
1999	—	`conf`	Imprecise Reliability Models for the General Lifetime Distribution Classes. ISIPTA Lev V. Utkin, Sergey V. Gurov
1999	J	`jnl`	Imprecise Reliability of General Structures. Knowl. Inf. Syst. Lev V. Utkin, Sergey V. Gurov
1998	J	`jnl`	Steady-state reliability of repairable systems by combined probability and possibility assumptions. Fuzzy Sets Syst. Lev V. Utkin, Sergey V. Gurov
1996	J	`jnl`	A general formal approach for fuzzy reliability analysis in the possibility context. Fuzzy Sets Syst. Lev V. Utkin, Sergey V. Gurov