Optimal filtering of a random background in image processing problems. - Alexander V. Bernstein; Alexander P. Kuleshov (Probl. Inf. Transm., 2008)

Tangent Bundle Manifold Learning via Grassmann&Stiefel Eigenmaps - Alexander V. Bernstein; Alexander P. Kuleshov (CoRR, 2012)

Tangent bundle Manifold Learning for image analysis. - Alexander P. Kuleshov; Alexander V. Bernstein (ICMV, 2013)

Manifold Learning: Generalization Ability and Tangent Proximity. - Alexander V. Bernstein; Alexander P. Kuleshov (Int. J. Softw. Informatics, 2013)

Low-Dimensional Data Representation in Data Analysis. - Alexander V. Bernstein; Alexander P. Kuleshov (ANNPR, 2014)

Dimensionality Reduction in Statistical Learning. - Alexander V. Bernstein; Alexander P. Kuleshov (ICMLA, 2014)

Manifold Learning in Data Mining Tasks. - Alexander P. Kuleshov; Alexander V. Bernstein (MLDM, 2014)

Information preserving and locally isometric&conformal embedding via Tangent Manifold Learning. - Alexander V. Bernstein; Alexander P. Kuleshov; Yury Yanovich (DSAA, 2015)

Statistical Learning via Manifold Learning. - Alexander V. Bernstein; Alexander P. Kuleshov; Yury Yanovich (ICMLA, 2015)

Data-Based Statistical Models of Data Networks. - Alexander P. Kuleshov; Alexander V. Bernstein; Yury Agalakov (ICMLA, 2015)

Locally isometric and conformal parameterization of image manifold. - Alexander V. Bernstein; Alexander P. Kuleshov; Yury Yanovich (ICMV, 2015)

Manifold Learning in Regression Tasks. - Alexander V. Bernstein; Alexander P. Kuleshov; Yury Yanovich (SLDS, 2015)

Incremental Construction of Low-Dimensional Data Representations. - Alexander P. Kuleshov; Alexander V. Bernstein (ANNPR, 2016)

Extended Regression on Manifolds Estimation. - Alexander P. Kuleshov; Alexander V. Bernstein (COPA, 2016)

Regression on High-Dimensional Inputs. - Alexander P. Kuleshov; Alexander V. Bernstein (ICDM Workshops, 2016)

Machine vision and appearance based learning. - Alexander Bernstein (ICMV, 2016)

Statistical Learning on Manifold-Valued Data. - Alexander P. Kuleshov; Alexander V. Bernstein (MLDM, 2016)

Conformal k-NN Anomaly Detector for Univariate Data Streams. - Vladislav Ishimtsev; Alexander Bernstein; Evgeny Burnaev; Ivan Nazarov (COPA, 2017)

High-Dimensional Density Estimation for Data Mining Tasks. - Alexander P. Kuleshov; Alexander Bernstein; Yury Yanovich (ICDM Workshops, 2017)

Machine Learning in Appearance-Based Robot Self-Localization. - Alexander P. Kuleshov; Alexander Bernstein; Evgeny Burnaev; Yury Yanovich (ICMLA, 2017)

Mobile Robot Localization via Machine Learning. - Alexander P. Kuleshov; Alexander Bernstein; Evgeny Burnaev (MLDM, 2017)

Nonlinear multi-output regression on unknown input manifold. - Alexander P. Kuleshov; Alexander Bernstein (Ann. Math. Artif. Intell., 2017)

Conformal k-NN Anomaly Detector for Univariate Data Streams. - Vladislav Ishimtsev; Ivan Nazarov; Alexander Bernstein; Evgeny Burnaev (CoRR, 2017)

Manifold Learning Regression with Non-stationary Kernels. - Alexander P. Kuleshov; Alexander Bernstein; Evgeny Burnaev (ANNPR, 2018)

Pattern Recognition Pipeline for Neuroimaging Data. - Maxim Sharaev; Alexander Andreev; Alexey Artemov; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Irina Samotaeva; Vladislav Gaskin; Alexander Bernstein (ANNPR, 2018)

Conformal prediction in manifold learning. - Alexander P. Kuleshov; Alexander Bernstein; Evgeny Burnaev (COPA, 2018)

Kernel Regression on Manifold Valued Data. - Alexander P. Kuleshov; Alexander Bernstein; Evgeny Burnaev (DSAA, 2018)

MRI-Based Diagnostics of Depression Concomitant with Epilepsy: In Search of the Potential Biomarkers. - Maksim Sharaev; Alexey Artemov; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Evgeny Burnaev; Alexander Bernstein; Renat Akzhigitov; Alexander Andreev (DSAA, 2018)

Voxelwise 3D Convolutional and Recurrent Neural Networks for Epilepsy and Depression Diagnostics from Structural and Functional MRI Data. - Marina Pominova; Alexey Artemov; Maksim Sharaev; Ekaterina Kondrateva; Alexander Bernstein; Evgeny Burnaev (ICDM Workshops, 2018)

Learning Connectivity Patterns via Graph Kernels for fMRI-Based Depression Diagnostics. - Maksim Sharaev; Alexey Artemov; Ekaterina Kondrateva; Sergei Ivanov 002; Svetlana Sushchinskaya; Alexander Bernstein; Andrzej Cichocki; Evgeny Burnaev (ICDM Workshops, 2018)

Functional Brain Areas Mapping in Patients with Glioma Based on Resting-State fMRI Data Decomposition. - Maksim Sharaev; Alexander Smirnov; Tatiana Melnikova-Pitskhelauri; Vyacheslav A. Orlov; Evgeny Burnaev; Igor Pronin; David Pitskhelauri; Alexander Bernstein (ICDM Workshops, 2018)

Geometrically Motivated Nonstationary Kernel Density Estimation on Manifold. - Aleksander Kuleshov; Alexander Bernstein; Yury Yanovich (ISAIM, 2018)

Reinforcement Learning for Computer Vision and Robot Navigation. - Alexander V. Bernstein; Evgeny Burnaev; Oleg N. Kachan (MLDM (2), 2018)

Machine Learning pipeline for discovering neuroimaging-based biomarkers in neurology and psychiatry. - Alexander Bernstein; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Maxim Sharaev; Alexander Andreev; Alexey Artemov; Renat Akzhigitov (CoRR, 2018)

fMRI: preprocessing, classification and pattern recognition. - Maxim Sharaev; Alexander Andreev; Alexey Artemov; Alexander Bernstein; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Renat Akzhigitov (CoRR, 2018)

MRI brain imagery processing software in data analysis. - Alexander Bernstein; Renat Akzhigitov; Ekaterina Kondrateva; Svetlana Sushchinskaya; Irina Samotaeva; Vladislav Gaskin (Trans. Mass Data Anal. Images Signals, 2018)

Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem. - Sergey Pavlov; Alexey Artemov; Maksim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMLA, 2019)

3D Deformable Convolutions for MRI Classification. - Marina Pominova; Ekaterina Kondrateva; Maksim Sharaev; Alexander Bernstein; Sergey Pavlov; Evgeny Burnaev (ICMLA, 2019)

Topological data analysis in computer vision. - Alexander Bernstein; Eugeny Burnaev; Maxim Sharaev; Ekaterina Kondrateva; Oleg Kachan (ICMV, 2019)

Machine learning models reproducibility and validation for MR images recognition. - Ekaterina Kondrateva; Polina Belozerova; Maxim Sharaev; Evgeny Burnaev; Alexander Bernstein; Irina Samotaeva (ICMV, 2019)

Interpretation of 3D CNNs for Brain MRI Data Classification. - Maxim Kan; Ruslan Aliev; Anna Rudenko; Nikita Drobyshev; Nikita Petrashen; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (AIST (Supplement), 2020)

Domain shift in computer vision models for MRI data analysis: an overview. - Ekaterina Kondrateva; Marina Pominova; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMV, 2020)

Fader networks for domain adaptation on fMRI: ABIDE-II study. - Marina Pominova; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMV, 2020)

Interpretable Deep Learning for Pattern Recognition in Brain Differences Between Men and Women. - Maxim Kan; Ruslan Aliev; Anna Rudenko; Nikita Drobyshev; Nikita Petrashen; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

Domain Shift in Computer Vision models for MRI data analysis: An Overview. - Ekaterina Kondrateva; Marina Pominova; Elena Popova; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

Convolutional neural networks for automatic detection of Focal Cortical Dysplasia. - Ruslan Aliev; Ekaterina Kondrateva; Maxim Sharaev; Oleg Bronov; Alexey Marinets; Sergey Subbotin 002; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

Artificial Text Detection via Examining the Topology of Attention Maps. - Laida Kushnareva; Daniil Cherniavskii; Vladislav Mikhailov; Ekaterina Artemova; Serguei Barannikov; Alexander Bernstein; Irina Piontkovskaya; Dmitri Piontkovski; Evgeny Burnaev (EMNLP (1), 2021)

Autoencoders with deformable convolutions for latent representation of EEG spectrograms in classification tasks. - Maria Zubrikhina; Dmitrii Masnyi; Rifat Hamoudi; Hamid Alhaj; Bashar Issa; Almira Kustubaeva; Altyngul T. Kamzanova; Manzura Zholdassova; Alexander Bernstein; Evgeny Burnaev; Alexey Artemov; Maxim Sharaev (ICMV, 2022)

Multivariate Wasserstein Functional Connectivity for Autism Screening. - Oleg Kachan; Alexander Bernstein (CoRR, 2022)

Knowledge-informed randomized machine learning and data fusion for anomaly areas detection in multimodal 3D images. - Nadezhda Alsahanova; V. Yarkin; E. Spodarev; O. Bronov; V. Bychenko; A. Marinets; E. Syrkashev; O. Karpov; Evgeny Burnaev; Alexander Bernstein; V. Alferova; Maxim Sharaev (Inf. Sci., 2025)

A hierarchical algorithm with randomized learning for robust tissue segmentation and classification in digital pathology. - Svetlana Illarionova; Rifat A. Hamoudi; M. Zapevalina; I. Fedin; Nadezhda Alsahanova; Alexander Bernstein; Evgeny Burnaev; V. Alferova; Ekaterina Khrameeva; D. Shadrin; I. Talaat; Ahmed Bouridane; et al. (Inf. Sci., 2025)