Alexander V. Bernstein

According to our database, Alexander V. Bernstein authored at least 48 papers between 2008 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Multivariate Wasserstein Functional Connectivity for Autism Screening.

Oleg Kachan, Alexander Bernstein

CoRR, 2022

2021

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

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Convolutional neural networks for automatic detection of Focal Cortical Dysplasia.

Ruslan Aliev, Ekaterina Kondrateva, Maxim Sharaev, Oleg Bronov, Alexey Marinets, Sergey Subbotin, 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

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

Fader networks for domain adaptation on fMRI: ABIDE-II study.

Marina Pominova, Ekaterina Kondrateva, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev

Proceedings of the Thirteenth International Conference on Machine Vision, 2020

Domain shift in computer vision models for MRI data analysis: an overview.

Ekaterina Kondrateva, Marina Pominova, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev

Proceedings of the Thirteenth International Conference on Machine Vision, 2020

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

Proceedings of the Recent Trends in Analysis of Images, Social Networks and Texts, 2020

2019

Machine learning models reproducibility and validation for MR images recognition.

Ekaterina Kondrateva, Polina Belozerova, Maxim Sharaev, Evgeny Burnaev, Alexander Bernstein, Irina Samotaeva

Proceedings of the Twelfth International Conference on Machine Vision, 2019

Topological data analysis in computer vision.

Alexander Bernstein, Eugeny Burnaev, Maxim Sharaev, Ekaterina Kondrateva, Oleg Kachan

Proceedings of the Twelfth International Conference on Machine Vision, 2019

3D Deformable Convolutions for MRI Classification.

Marina Pominova, Ekaterina Kondrateva, Maksim Sharaev, Alexander Bernstein, Sergey Pavlov, Evgeny Burnaev

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem.

Sergey Pavlov, Alexey Artemov, Maksim Sharaev, Alexander Bernstein, Evgeny Burnaev

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

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

fMRI: preprocessing, classification and pattern recognition.

Maxim Sharaev, Alexander Andreev, Alexey Artemov, Alexander Bernstein, Evgeny Burnaev, Ekaterina Kondratyeva, Svetlana Sushchinskaya, Renat Akzhigitov

CoRR, 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

Reinforcement Learning for Computer Vision and Robot Navigation.

Alexander V. Bernstein, Evgeny Burnaev, Oleg N. Kachan

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2018

Geometrically Motivated Nonstationary Kernel Density Estimation on Manifold.

Aleksander Kuleshov, Alexander Bernstein, Yury Yanovich

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 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

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Learning Connectivity Patterns via Graph Kernels for fMRI-Based Depression Diagnostics.

Maksim Sharaev, Alexey Artemov, Ekaterina Kondrateva, Sergei Ivanov, Svetlana Sushchinskaya, Alexander Bernstein, Andrzej Cichocki, Evgeny Burnaev

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 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

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 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

Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

Kernel Regression on Manifold Valued Data.

Alexander P. Kuleshov, Alexander Bernstein, Evgeny Burnaev

Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

Conformal prediction in manifold learning.

Alexander P. Kuleshov, Alexander Bernstein, Evgeny Burnaev

Proceedings of the 7th Symposium on Conformal and Probabilistic Prediction and Applications, 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

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

Manifold Learning Regression with Non-stationary Kernels.

Alexander P. Kuleshov, Alexander Bernstein, Evgeny Burnaev

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

2017

Conformal k-NN Anomaly Detector for Univariate Data Streams.

Vladislav Ishimtsev, Ivan Nazarov, Alexander Bernstein, Evgeny Burnaev

CoRR, 2017

Nonlinear multi-output regression on unknown input manifold.

Alexander P. Kuleshov, Alexander Bernstein

Ann. Math. Artif. Intell., 2017

Mobile Robot Localization via Machine Learning.

Alexander P. Kuleshov, Alexander Bernstein, Evgeny Burnaev

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2017

Machine Learning in Appearance-Based Robot Self-Localization.

Alexander P. Kuleshov, Alexander Bernstein, Evgeny Burnaev, Yury Yanovich

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

High-Dimensional Density Estimation for Data Mining Tasks.

Alexander P. Kuleshov, Alexander Bernstein, Yury Yanovich

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Conformal <i>k</i>-NN Anomaly Detector for Univariate Data Streams.

Vladislav Ishimtsev, Alexander Bernstein, Evgeny Burnaev, Ivan Nazarov

Proceedings of the Conformal and Probabilistic Prediction and Applications, 2017

2016

Statistical Learning on Manifold-Valued Data.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2016

Machine vision and appearance based learning.

Alexander Bernstein

Proceedings of the Ninth International Conference on Machine Vision, 2016

Regression on High-Dimensional Inputs.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Extended Regression on Manifolds Estimation.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2016

Incremental Construction of Low-Dimensional Data Representations.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015

Manifold Learning in Regression Tasks.

Alexander V. Bernstein, Alexander P. Kuleshov, Yury Yanovich

Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

Locally isometric and conformal parameterization of image manifold.

Alexander V. Bernstein, Alexander P. Kuleshov, Yury Yanovich

Proceedings of the Eighth International Conference on Machine Vision, 2015

Data-Based Statistical Models of Data Networks.

Alexander P. Kuleshov, Alexander V. Bernstein, Yury Agalakov

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Statistical Learning via Manifold Learning.

Alexander V. Bernstein, Alexander P. Kuleshov, Yury Yanovich

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Information preserving and locally isometric&conformal embedding via Tangent Manifold Learning.

Alexander V. Bernstein, Alexander P. Kuleshov, Yury Yanovich

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

2014

Manifold Learning in Data Mining Tasks.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2014

Dimensionality Reduction in Statistical Learning.

Alexander V. Bernstein, Alexander P. Kuleshov

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

Low-Dimensional Data Representation in Data Analysis.

Alexander V. Bernstein, Alexander P. Kuleshov

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2014

2013

Manifold Learning: Generalization Ability and Tangent Proximity.

Alexander V. Bernstein, Alexander P. Kuleshov

Int. J. Softw. Informatics, 2013

Tangent bundle Manifold Learning for image analysis.

Alexander P. Kuleshov, Alexander V. Bernstein

Proceedings of the Sixth International Conference on Machine Vision, 2013

2012

Tangent Bundle Manifold Learning via Grassmann&Stiefel Eigenmaps

Alexander V. Bernstein, Alexander P. Kuleshov

CoRR, 2012

2008

Optimal filtering of a random background in image processing problems.

Alexander V. Bernstein, Alexander P. Kuleshov

Probl. Inf. Transm., 2008