One Approach to Fuzzy Expert Systems Construction. - Dmitry Kropotov; Dmitry P. Vetrov (ICEIS (2), 2003)

Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms. - Dmitry P. Vetrov; Dmitry Kropotov (ICPR (1), 2004)

An Algorithm for Rule Generation in Fuzzy Expert Systems. - Dmitry Kropotov; Dmitry P. Vetrov (ICPR (1), 2004)

The Use of Bayesian Framework for Kernel Selection in Vector Machines Classifiers. - Dmitry Kropotov; Nikita Ptashko; Dmitry P. Vetrov (CIARP, 2005)

The Use of Stability Principle for Kernel Determination in Relevance Vector Machines. - Dmitry Kropotov; Dmitry P. Vetrov; Nikita Ptashko; Oleg Vasiliev (ICONIP (1), 2006)

On Kernel Selection in Relevance Vector Machines Using Stability Principle. - Dmitry Kropotov; Nikita Ptashko; Oleg Vasiliev; Dmitry P. Vetrov (ICPR (4), 2006)

On one method of non-diagonal regularization in sparse Bayesian learning. - Dmitry Kropotov; Dmitry P. Vetrov (ICML, 2007)

Fuzzy Rules Generation Method for Pattern Recognition Problems. - Dmitry Kropotov; Dmitry P. Vetrov (WILF, 2007)

3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas. - Anton Osokin; Dmitry P. Vetrov; Dmitry Kropotov (CIBB, 2009)

An Interactive Method of Anatomical Segmentation and Gene Expression Estimation for an Experimental Mouse Brain Slice. - Anton Osokin; Dmitry P. Vetrov; Alexey Lebedev; Vladimir Galatenko; Dmitry Kropotov; Konstantin V. Anokhin (CIBB, 2010)

Variational Relevance Vector Machine for Tabular Data. - Dmitry Kropotov; Dmitry P. Vetrov; Lior Wolf; Tal Hassner (ACML, 2010)

A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums. - Anton Rodomanov; Dmitry Kropotov (ICML, 2016)

Faster variational inducing input Gaussian process classification. - Pavel Izmailov; Dmitry Kropotov (CoRR, 2016)

Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. - Pavel Izmailov; Alexander Novikov 001; Dmitry Kropotov (AISTATS, 2018)

Hamiltonian Monte-Carlo for Orthogonal Matrices. - Viktor Yanush; Dmitry Kropotov (CoRR, 2019)

A Randomized Coordinate Descent Method with Volume Sampling. - Anton Rodomanov; Dmitry Kropotov (SIAM J. Optim., 2020)

Massive MIMO Adaptive Modulation and Coding Using Online Deep Learning. - Evgeny Bobrov; Dmitry Kropotov; Hao Lu; Danila Zaev (CoRR, 2021)

Finding Better Precoding in Massive MIMO using Optimization Approach. - Evgeny Bobrov; Dmitry Kropotov; Sergey Troshin; Danila Zaev (CoRR, 2021)

Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems. - Evgeny Bobrov; Sergey Troshin 001; Nadezhda Chirkova; Ekaterina Lobacheva; Sviatoslav Panchenko; Dmitry P. Vetrov; Dmitry Kropotov (CoRR, 2021)

Massive MIMO Adaptive Modulation and Coding Using Online Deep Learning Algorithm. - Evgeny Bobrov; Dmitry Kropotov; Hao Lu; Danila Zaev (IEEE Commun. Lett., 2022)

Handwritten Text Recognition and Browsing in Archive of Prisoners' Letters from Smolensk Convict Prison. - Nikita Lomov; Dmitry Kropotov; Danila Stepochkin; Anton Laptev (AIST, 2023)

MARS: Masked Automatic Ranks Selection in Tensor Decompositions. - Maxim Kodryan; Dmitry Kropotov; Dmitry P. Vetrov (AISTATS, 2023)

YOLO-HTR: Page-Level Recognition of Historical Handwritten Document Collections. - Nikita Lomov; Danila Stepochkin; Dmitry Kropotov (AIST, 2024)

Study on precoding optimization algorithms in massive MIMO system with multi-antenna users. - Evgeny Bobrov; Dmitry Kropotov; Sergey Troshin 001; Danila Zaev (Optim. Methods Softw., 2024)