Tucker Dimensionality Reduction of Three-Dimensional Arrays in Linear Time. - Ivan V. Oseledets; Dmitry V. Savostyanov; Eugene E. Tyrtyshnikov (SIAM J. Matrix Anal. Appl., 2008)

Linear algebra for tensor problems. - Ivan V. Oseledets; Dmitry V. Savostyanov; Eugene E. Tyrtyshnikov (Computing, 2009)

Fast Simultaneous Orthogonal Reduction to Triangular Matrices. - Ivan V. Oseledets; Dmitry V. Savostyanov; Eugene E. Tyrtyshnikov (SIAM J. Matrix Anal. Appl., 2009)

Breaking the Curse of Dimensionality, Or How to Use SVD in Many Dimensions. - Ivan V. Oseledets; Eugene E. Tyrtyshnikov (SIAM J. Sci. Comput., 2009)

Quantics-TT Collocation Approximation of Parameter-Dependent and Stochastic Elliptic PDEs. - Boris N. Khoromskij; Ivan V. Oseledets (Comput. Methods Appl. Math., 2010)

Cross approximation in tensor electron density computations. - Ivan V. Oseledets; Dmitry V. Savostyanov; Eugene E. Tyrtyshnikov (Numer. Linear Algebra Appl., 2010)

Approximation of 2d˟2d Matrices Using Tensor Decomposition. - Ivan V. Oseledets (SIAM J. Matrix Anal. Appl., 2010)

Tensor train decomposition for low-parametric representation of high-dimensional arrays and functions: Review of recent results. - Ivan V. Oseledets (nDS, 2011)

Fast adaptive interpolation of multi-dimensional arrays in tensor train format. - Dmitry V. Savostyanov; Ivan V. Oseledets (nDS, 2011)

DMRG Approach to Fast Linear Algebra in the TT-Format. - Ivan V. Oseledets (Comput. Methods Appl. Math., 2011)

Tensor-Train Ranks for Matrices and Their Inverses. - Ivan V. Oseledets; Eugene E. Tyrtyshnikov; Nickolai L. Zamarashkin (Comput. Methods Appl. Math., 2011)

Tensor-Train Decomposition. - Ivan V. Oseledets (SIAM J. Sci. Comput., 2011)

Algebraic Wavelet Transform via Quantics Tensor Train Decomposition. - Ivan V. Oseledets; Eugene E. Tyrtyshnikov (SIAM J. Sci. Comput., 2011)

Improved n-Term Karatsuba-Like Formulas in GF(2). - Ivan V. Oseledets (IEEE Trans. Computers, 2011)

Fast Solution of Parabolic Problems in the Tensor Train/Quantized Tensor Train Format with Initial Application to the Fokker-Planck Equation. - Sergey V. Dolgov; Boris N. Khoromskij; Ivan V. Oseledets (SIAM J. Sci. Comput., 2012)

Wedderburn Rank Reduction and Krylov Subspace Method for Tensor Approximation. Part 1: Tucker Case. - Sergei A. Goreinov; Ivan V. Oseledets; Dmitry V. Savostyanov (SIAM J. Sci. Comput., 2012)

Solution of Linear Systems and Matrix Inversion in the TT-Format. - Ivan V. Oseledets; Sergey V. Dolgov (SIAM J. Sci. Comput., 2012)

A computationally efficient technique for the solution of multi-dimensional PBMs of granulation via tensor decomposition. - Anwesha Chaudhury; Ivan V. Oseledets; Rohit Ramachandran (Comput. Chem. Eng., 2014)

Iterative across-time solution of linear differential equations: Krylov subspace versus waveform relaxation. - Mike A. Botchev; Ivan V. Oseledets; Eugene E. Tyrtyshnikov (Comput. Math. Appl., 2014)

Fast, memory efficient low-rank approximation of SimRank. - Ivan V. Oseledets; G. V. Ovchinnikov (CoRR, 2014)

Algebraic reputation model RepRank and its application to spambot detection. - G. V. Ovchinnikov; D. A. Kolesnikov; Ivan V. Oseledets (CoRR, 2014)

Computation of extreme eigenvalues in higher dimensions using block tensor train format. - Sergey V. Dolgov; Boris N. Khoromskij; Ivan V. Oseledets; Dmitry V. Savostyanov (Comput. Phys. Commun., 2014)

The DEPOSIT computer code based on the low rank approximations. - Mikhail S. Litsarev; Ivan V. Oseledets (Comput. Phys. Commun., 2014)

Low-rank retractions: a survey and new results. - Pierre-Antoine Absil; Ivan V. Oseledets (Comput. Optim. Appl., 2015)

Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition. - Vadim Lebedev; Yaroslav Ganin; Maksim Rakhuba; Ivan V. Oseledets; Victor S. Lempitsky (ICLR (Poster), 2015)

Rectangular maximum-volume submatrices and their applications. - A. Yu. Mikhalev; Ivan V. Oseledets (CoRR, 2015)

Linear complexity SimRank computation based on the iterative diagonal estimation. - Ivan V. Oseledets; G. V. Ovchinnikov; Alexandr M. Katrutsa (CoRR, 2015)

Tensor SimRank for Heterogeneous Information Networks. - Ben Usman; Ivan V. Oseledets (CoRR, 2015)

Fast low-rank approximations of multidimensional integrals in ion-atomic collisions modelling. - Mikhail S. Litsarev; Ivan V. Oseledets (Numer. Linear Algebra Appl., 2015)

From Low-Rank Approximation to a Rational Krylov Subspace Method for the Lyapunov Equation. - D. A. Kolesnikov; Ivan V. Oseledets (SIAM J. Matrix Anal. Appl., 2015)

Time Integration of Tensor Trains. - Christian Lubich; Ivan V. Oseledets; Bart Vandereycken (SIAM J. Numer. Anal., 2015)

Fast Multidimensional Convolution in Low-Rank Tensor Formats via Cross Approximation. - M. V. Rakhuba; Ivan V. Oseledets (SIAM J. Sci. Comput., 2015)

Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition. - Zheng Zhang 005; Xiu Yang; Ivan V. Oseledets; George E. Karniadakis; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2015)

Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering. - Alexander Fonarev; Alexander Mikhalev; Pavel Serdyukov; Gleb Gusev; Ivan V. Oseledets (ICDM, 2016)

Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks. - Evgeny Frolov; Ivan V. Oseledets (RecSys, 2016)

A new approach for sparse Bayesian channel estimation in SCMA uplink systems. - Kirill Struminsky; Stanislav Kruglik; Dmitry P. Vetrov; Ivan V. Oseledets (WCSP, 2016)

Low-Rank Tensor Networks for Dimensionality Reduction and Large-Scale Optimization Problems: Perspectives and Challenges PART 1. - Andrzej Cichocki; Namgil Lee; Ivan V. Oseledets; Anh Huy Phan 001; Qibin Zhao; Danilo P. Mandic (CoRR, 2016)

Tensor Train polynomial models via Riemannian optimization. - Alexander Novikov 001; Mikhail Trofimov; Ivan V. Oseledets (CoRR, 2016)

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions. - Andrzej Cichocki; Namgil Lee; Ivan V. Oseledets; Anh Huy Phan 001; Qibin Zhao; Danilo P. Mandic (Found. Trends Mach. Learn., 2016)

A low-rank approach to the computation of path integrals. - Mikhail S. Litsarev; Ivan V. Oseledets (J. Comput. Phys., 2016)

Grid-based electronic structure calculations: The tensor decomposition approach. - M. V. Rakhuba; Ivan V. Oseledets (J. Comput. Phys., 2016)

Iterative representing set selection for nested cross approximation. - A. Yu. Mikhalev; Ivan V. Oseledets (Numer. Linear Algebra Appl., 2016)

Riemannian Optimization for Skip-Gram Negative Sampling. - Alexander Fonarev; Oleksii Hrinchuk; Gleb Gusev; Pavel Serdyukov; Ivan V. Oseledets (ACL (1), 2017)

Exponential Machines. - Alexander Novikov 001; Mikhail Trofimov; Ivan V. Oseledets (ICLR (Workshop), 2017)

QTT-finite-element approximation for multiscale problems I: model problems in one dimension. - Vladimir A. Kazeev; Ivan V. Oseledets; Maksim Rakhuba; Christoph Schwab (Adv. Comput. Math., 2017)

Fast, memory-efficient low-rank approximation of SimRank. - Ivan V. Oseledets; G. V. Ovchinnikov; Alexandr M. Katrutsa (J. Complex Networks, 2017)

Vico-Greengard-Ferrando quadratures in the tensor solver for integral equations. - Valentin Khrulkov; M. V. Rakhuba; Ivan V. Oseledets (CoRR, 2017)

Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives. - Andrzej Cichocki; Anh Huy Phan 001; Qibin Zhao; Namgil Lee; Ivan V. Oseledets; Masashi Sugiyama; Danilo P. Mandic (CoRR, 2017)

Neural networks for topology optimization. - Ivan Sosnovik; Ivan V. Oseledets (CoRR, 2017)

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives. - Andrzej Cichocki; Anh Huy Phan 001; Qibin Zhao; Namgil Lee; Ivan V. Oseledets; Masashi Sugiyama; Danilo P. Mandic (Found. Trends Mach. Learn., 2017)

Time- and memory-efficient representation of complex mesoscale potentials. - Grigoriy M. Drozdov; Igor A. Ostanin; Ivan V. Oseledets (J. Comput. Phys., 2017)

Tensor methods and recommender systems. - Evgeny Frolov; Ivan V. Oseledets (WIREs Data Mining Knowl. Discov., 2017)

Matrix Factorization for Collaborative Recommendations. - Evgeny Frolov; Ivan V. Oseledets (Collaborative Recommendations, 2018)

Art of Singular Vectors and Universal Adversarial Perturbations. - Valentin Khrulkov; Ivan V. Oseledets (CVPR, 2018)

Expressive power of recurrent neural networks. - Valentin Khrulkov; Alexander Novikov 001; Ivan V. Oseledets (ICLR (Poster), 2018)

Geometry Score: A Method For Comparing Generative Adversarial Networks. - Valentin Khrulkov; Ivan V. Oseledets (ICML, 2018)

AA-ICP: Iterative Closest Point with Anderson Acceleration. - Artem L. Pavlov; Grigory V. Ovchinnikov; Dmitry Yu. Derbyshev; Dzmitry Tsetserukou; Ivan V. Oseledets (ICRA, 2018)

Quadrature-based features for kernel approximation. - Marina Munkhoeva; Yermek Kapushev; Evgeny Burnaev; Ivan V. Oseledets (NeurIPS, 2018)

Gradient Descent-based D-optimal Design for the Least-Squares Polynomial Approximation. - Vitaly P. Zankin; Gleb V. Ryzhakov; Ivan V. Oseledets (CoRR, 2018)

Comparative study of Discrete Wavelet Transforms and Wavelet Tensor Train decomposition to feature extraction of FTIR data of medicinal plants. - Pavel Kharyuk; Dmitry Nazarenko; Ivan V. Oseledets (CoRR, 2018)

Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge. - Evgeny Frolov; Ivan V. Oseledets (CoRR, 2018)

Modelling hidden structure of signals in group data analysis with modified (Lr, 1) and block-term decompositions. - Pavel Kharyuk; Ivan V. Oseledets (CoRR, 2018)

Adversarial point set registration. - Sergei Divakov; Ivan V. Oseledets (CoRR, 2018)

PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach. - Tsui-Wei Weng; Pin-Yu Chen; Lam M. Nguyen; Mark S. Squillante; Ivan V. Oseledets; Luca Daniel (CoRR, 2018)

Convergence analysis of projected fixed-point iteration on a low-rank matrix manifold. - D. A. Kolesnikov; Ivan V. Oseledets (Numer. Linear Algebra Appl., 2018)

Pervasive Agriculture: IoT-Enabled Greenhouse for Plant Growth Control. - Andrey Somov; Dmitrii G. Shadrin; Ilia Fastovets; Artyom Nikitin; Sergey A. Matveev; Ivan V. Oseledets; Oleksii Hrinchuk (IEEE Pervasive Comput., 2018)

Desingularization of Bounded-Rank Matrix Sets. - Valentin Khrulkov; Ivan V. Oseledets (SIAM J. Matrix Anal. Appl., 2018)

Alternating Least Squares as Moving Subspace Correction. - Ivan V. Oseledets; Maxim V. Rakhuba; André Uschmajew (SIAM J. Numer. Anal., 2018)

Jacobi-Davidson Method on Low-Rank Matrix Manifolds. - M. V. Rakhuba; Ivan V. Oseledets (SIAM J. Sci. Comput., 2018)

"Compress and Eliminate" Solver for Symmetric Positive Definite Sparse Matrices. - Daria A. Sushnikova; Ivan V. Oseledets (SIAM J. Sci. Comput., 2018)

Automated Multi-Stage Compression of Neural Networks. - Julia Gusak; Maksym Kholyavchenko; Evgeny Ponomarev; Larisa Markeeva; Philip Blagoveschensky; Andrzej Cichocki; Ivan V. Oseledets (ICCV Workshops, 2019)

Generalized Tensor Models for Recurrent Neural Networks. - Valentin Khrulkov; Oleksii Hrinchuk; Ivan V. Oseledets (ICLR (Poster), 2019)

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach. - Lily Weng; Pin-Yu Chen; Lam M. Nguyen; Mark S. Squillante; Akhilan Boopathy; Ivan V. Oseledets; Luca Daniel (ICML, 2019)

IceVisionSet: lossless video dataset collected on Russian winter roads with traffic sign annotations. - Artem L. Pavlov; Pavel A. Karpyshev; George V. Ovchinnikov; Ivan V. Oseledets; Dzmitry Tsetserukou (ICRA, 2019)

HybridSVD: when collaborative information is not enough. - Evgeny Frolov; Ivan V. Oseledets (RecSys, 2019)

Tensor Train Spectral Method for Learning of Hidden Markov Models (HMM). - Maxim A. Kuznetsov; Ivan V. Oseledets (Comput. Methods Appl. Math., 2019)

Approximate Solution of Linear Systems with Laplace-like Operators via Cross Approximation in the Frequency Domain. - Ekaterina A. Muravleva; Ivan V. Oseledets (Comput. Methods Appl. Math., 2019)

Deep Neural Networks Predicting Oil Movement in a Development Unit. - Pavel Temirchev; Maxim Simonov; Ruslan Kostoev; Evgeny Burnaev; Ivan V. Oseledets; Alexey Akhmetov; Andrey Margarit; Alexander Sitnikov; Dmitry A. Koroteev (CoRR, 2019)

Tensorized Embedding Layers for Efficient Model Compression. - Valentin Khrulkov; Oleksii Hrinchuk; Leyla Mirvakhabova; Ivan V. Oseledets (CoRR, 2019)

Preconditioning Kaczmarz method by sketching. - Alexandr Katrutsa; Ivan V. Oseledets (CoRR, 2019)

One time is not enough: iterative tensor decomposition for neural network compression. - Julia Gusak; Maksym Kholyavchenko; Evgeny Ponomarev; Larisa Markeeva; Ivan V. Oseledets; Andrzej Cichocki (CoRR, 2019)

Intrinsic Multi-scale Evaluation of Generative Models. - Anton Tsitsulin; Marina Munkhoeva; Davide Mottin; Panagiotis Karras; Alexander M. Bronstein; Ivan V. Oseledets; Emmanuel Müller (CoRR, 2019)

Universality Theorems for Generative Models. - Valentin Khrulkov; Ivan V. Oseledets (CoRR, 2019)

Empirical study of extreme overfitting points of neural networks. - Daniil Merkulov; Ivan V. Oseledets (CoRR, 2019)

Microstructure synthesis using style-based generative adversarial network. - Daria Fokina; Ekaterina A. Muravleva; George V. Ovchinnikov; Ivan V. Oseledets (CoRR, 2019)

Recognition of Russian traffic signs in winter conditions. Solutions of the "Ice Vision" competition winners. - Artem L. Pavlov; Azat Davletshin; Alexey Kharlamov; Maksim S. Koriukin; Artem Vasenin; Pavel Solovev; Pavel Ostyakov; Pavel A. Karpyshev; George V. Ovchinnikov; Ivan V. Oseledets; Dzmitry Tsetserukou (CoRR, 2019)

Practical shift choice in the shift-and-invert Krylov subspace evaluations of the matrix exponential. - Alexandr Katrutsa; Mike A. Botchev; Ivan V. Oseledets (CoRR, 2019)

Predicting dynamical system evolution with residual neural networks. - Artem V. Chashchin; Mikhail A. Botchev; Ivan V. Oseledets; Grigory V. Ovchinnikov (CoRR, 2019)

Reduced-Order Modeling of Deep Neural Networks. - Talgat Daulbaev; Julia Gusak; Evgeny Ponomarev; Andrzej Cichocki; Ivan V. Oseledets (CoRR, 2019)

Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics. - Taras Khakhulin; Roman Schutski; Ivan V. Oseledets (CoRR, 2019)

Growing axons: greedy learning of neural networks with application to function approximation. - Daria Fokina; Ivan V. Oseledets (CoRR, 2019)

An adaptive algorithm for quantum circuit simulation. - Roman Schutski; Danil Lykov; Ivan V. Oseledets (CoRR, 2019)

Low-rank Riemannian eigensolver for high-dimensional Hamiltonians. - Maxim V. Rakhuba; Alexander Novikov 001; Ivan V. Oseledets (J. Comput. Phys., 2019)

Hyperbolic Image Embeddings. - Valentin Khrulkov; Leyla Mirvakhabova; Evgeniya Ustinova; Ivan V. Oseledets; Victor S. Lempitsky (CVPR, 2020)

Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network. - Anh Huy Phan 001; Konstantin Sobolev; Konstantin Sozykin; Dmitry Ermilov; Julia Gusak; Petr Tichavský; Valeriy Glukhov; Ivan V. Oseledets; Andrzej Cichocki (ECCV (29), 2020)

Tensorized Embedding Layers. - Oleksii Hrinchuk; Valentin Khrulkov; Leyla Mirvakhabova; Elena Orlova; Ivan V. Oseledets (EMNLP (Findings), 2020)

Sensitivity Analysis of Soil Parameters in Crop Model Supported with High-Throughput Computing. - Mikhail Gasanov; Anna Petrovskaia; Artyom Nikitin; Sergey A. Matveev; Polina Tregubova; Maria Pukalchik; Ivan V. Oseledets (ICCS (7), 2020)

The Shape of Data: Intrinsic Distance for Data Distributions. - Anton Tsitsulin; Marina Munkhoeva; Davide Mottin; Panagiotis Karras; Alexander M. Bronstein; Ivan V. Oseledets; Emmanuel Müller (ICLR, 2020)

TT-TSDF: Memory-Efficient TSDF with Low-Rank Tensor Train Decomposition. - Alexey I. Boyko; Mikhail P. Matrosov; Ivan V. Oseledets; Dzmitry Tsetserukou; Gonzalo Ferrer 001 (IROS, 2020)

Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs. - Talgat Daulbaev; Alexandr Katrutsa; Larisa Markeeva; Julia Gusak; Andrzej Cichocki; Ivan V. Oseledets (NeurIPS, 2020)

Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. - Leyla Mirvakhabova; Evgeny Frolov; Valentin Khrulkov; Ivan V. Oseledets; Alexander Tuzhilin (RecSys, 2020)

Simple non-extensive sparsification of the hierarchical matrices. - Daria A. Sushnikova; Ivan V. Oseledets (Adv. Comput. Math., 2020)

Randomized Algorithms for Computation of Tucker decomposition and Higher Order SVD (HOSVD). - Salman Ahmadi-Asl; Andrzej Cichocki; Anh Huy Phan 001; Ivan V. Oseledets; Stanislav Abukhovich; Toshihisa Tanaka 001 (CoRR, 2020)

Deep Representation Learning for Dynamical Systems Modeling. - Anna Shalova; Ivan V. Oseledets (CoRR, 2020)

Using Reinforcement Learning in the Algorithmic Trading Problem. - Evgeny Ponomarev; Ivan V. Oseledets; Andrzej Cichocki (CoRR, 2020)

Interpolated Adjoint Method for Neural ODEs. - Talgat Daulbaev; Alexandr Katrutsa; Larisa Markeeva; Julia Gusak; Andrzej Cichocki; Ivan V. Oseledets (CoRR, 2020)

Bayesian aggregation improves traditional single image crop classification approaches. - Ivan Matvienko; Mikhail Gasanov; Anna Petrovskaia; Raghavendra Belur Jana; Maria Pukalchik; Ivan V. Oseledets (CoRR, 2020)

A single image deep learning approach to restoration of corrupted remote sensing products. - Anna Petrovskaia; Raghavendra B. Jana; Ivan V. Oseledets (CoRR, 2020)

Stochastic gradient algorithms from ODE splitting perspective. - Daniil Merkulov; Ivan V. Oseledets (CoRR, 2020)

Towards Understanding Normalization in Neural ODEs. - Julia Gusak; Larisa Markeeva; Talgat Daulbaev; Alexandr Katrutsa; Andrzej Cichocki; Ivan V. Oseledets (CoRR, 2020)

Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation. - Roman Schutski; Dmitry Kolmakov; Taras Khakhulin; Ivan V. Oseledets (CoRR, 2020)

Tensorized Transformer for Dynamical Systems Modeling. - Anna Shalova; Ivan V. Oseledets (CoRR, 2020)

FREDE: Linear-Space Anytime Graph Embeddings. - Anton Tsitsulin; Marina Munkhoeva; Davide Mottin; Panagiotis Karras; Ivan V. Oseledets; Emmanuel Müller (CoRR, 2020)

Follow the bisector: a simple method for multi-objective optimization. - Alexandr Katrutsa; Daniil Merkulov; Nurislam Tursynbek; Ivan V. Oseledets (CoRR, 2020)

Robustness Threats of Differential Privacy. - Nurislam Tursynbek; Aleksandr Petiushko; Ivan V. Oseledets (CoRR, 2020)

Black-box learning of multigrid parameters. - Alexandr Katrutsa; Talgat Daulbaev; Ivan V. Oseledets (J. Comput. Appl. Math., 2020)

Tensor Train Decomposition on TensorFlow (T3F). - Alexander Novikov 001; Pavel Izmailov; Valentin Khrulkov; Michael Figurnov; Ivan V. Oseledets (J. Mach. Learn. Res., 2020)

Tensor Completion via Gaussian Process-Based Initialization. - Yermek Kapushev; Ivan V. Oseledets; Evgeny Burnaev (SIAM J. Sci. Comput., 2020)

Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. - Chunfeng Cui; Kaiqi Zhang 002; Talgat Daulbaev; Julia Gusak; Ivan V. Oseledets; Zheng Zhang 005 (SIAM J. Math. Data Sci., 2020)

Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition. - Anh-Huy Phan 001; Andrzej Cichocki; Ivan V. Oseledets; Giuseppe Giovanni Calvi; Salman Ahmadi-Asl; Danilo P. Mandic (IEEE Trans. Neural Networks Learn. Syst., 2020)

Adversarial Turing Patterns from Cellular Automata. - Nurislam Tursynbek; Ilya Vilkoviskiy; Maria Sindeeva; Ivan V. Oseledets (AAAI, 2021)

A New Multi-objective Approach to Optimize Irrigation Using a Crop Simulation Model and Weather History. - Mikhail Gasanov; Daniil Merkulov; Artyom Nikitin; Sergey A. Matveev; Nikita Stasenko; Anna Petrovskaia; Mariia Pukalchik; Ivan V. Oseledets (ICCS (4), 2021)

Latent Transformations via NeuralODEs for GAN-based Image Editing. - Valentin Khrulkov; Leyla Mirvakhabova; Ivan V. Oseledets; Artem Babenko (ICCV, 2021)

Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study. - Svetlana Illarionova; Sergey Nesteruk; Dmitrii Shadrin; Vladimir Ignatiev; Mariia Pukalchik; Ivan V. Oseledets (ICCVW, 2021)

Functional Space Analysis of Local GAN Convergence. - Valentin Khrulkov; Artem Babenko; Ivan V. Oseledets (ICML, 2021)

Deep Neural Networks and Adaptive Quadrature for Solving Variational Problems. - Daria Fokina; Oleg Iliev 001; Ivan V. Oseledets (LSSC, 2021)

Tensor-train density estimation. - Georgii S. Novikov; Maxim E. Panov; Ivan V. Oseledets (UAI, 2021)

Dynamic Modeling of User Preferences for Stable Recommendations. - Oluwafemi Olaleke; Ivan V. Oseledets; Evgeny Frolov (UMAP, 2021)

Randomized Algorithms for Computation of Tucker Decomposition and Higher Order SVD (HOSVD). - Salman Ahmadi-Asl; Stanislav Abukhovich; Maame G. Asante-Mensah; Andrzej Cichocki; Anh-Huy Phan 001; Toshihisa Tanaka 001; Ivan V. Oseledets (IEEE Access, 2021)

Cross Tensor Approximation Methods for Compression and Dimensionality Reduction. - Salman Ahmadi-Asl; Cesar F. Caiafa; Andrzej Cichocki; Anh Huy Phan 001; Toshihisa Tanaka 001; Ivan V. Oseledets; Jun Wang 002 (IEEE Access, 2021)

Two-phase approaches to optimal model-based design of experiments: how many experiments and which ones? - Charlie Vanaret; Philipp Seufert; Jan Schwientek; Gleb Karpov; Gleb V. Ryzhakov; Ivan V. Oseledets; Norbert Asprion; Michael Bortz (Comput. Chem. Eng., 2021)

Latency Estimation Tool and Investigation of Neural Networks Inference on Mobile GPU. - Evgeny Ponomarev; Sergey A. Matveev; Ivan V. Oseledets; Valery Glukhov (Comput., 2021)

Denoising Score Matching with Random Fourier Features. - Tsimboy Olga; Yermek Kapushev; Evgeny Burnaev; Ivan V. Oseledets (CoRR, 2021)

Disentangled Representations from Non-Disentangled Models. - Valentin Khrulkov; Leyla Mirvakhabova; Ivan V. Oseledets; Artem Babenko (CoRR, 2021)

Meta-Solver for Neural Ordinary Differential Equations. - Julia Gusak; Alexandr Katrutsa; Talgat Daulbaev; Andrzej Cichocki; Ivan V. Oseledets (CoRR, 2021)

Optimal soil sampling design based on the maxvol algorithm. - Anna Petrovskaia; Gleb V. Ryzhakov; Ivan V. Oseledets (CoRR, 2021)

Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation. - Svetlana Illarionova; Sergey Nesteruk; Dmitrii Shadrin; Vladimir Ignatiev; Mariia Pukalchik; Ivan V. Oseledets (CoRR, 2021)

Solution of the Fokker-Planck Equation by Cross Approximation Method in the Tensor Train Format. - Andrei Chertkov; Ivan V. Oseledets (Frontiers Artif. Intell., 2021)

QTT-isogeometric solver in two dimensions. - Larisa Markeeva; I. Tsybulin; Ivan V. Oseledets (J. Comput. Phys., 2021)

Randomized algorithms for fast computation of low rank tensor ring model. - Salman Ahmadi-Asl; Andrzej Cichocki; Anh Huy Phan 001; Maame G. Asante-Mensah; Mirfarid Musavian Ghazani; Toshihisa Tanaka 001; Ivan V. Oseledets (Mach. Learn. Sci. Technol., 2021)

FREDE: Anytime Graph Embeddings. - Anton Tsitsulin; Marina Munkhoeva; Davide Mottin; Panagiotis Karras; Ivan V. Oseledets; Emmanuel Müller (Proc. VLDB Endow., 2021)

MixChannel: Advanced Augmentation for Multispectral Satellite Images. - Svetlana Illarionova; Sergey Nesteruk; Dmitrii Shadrin; Vladimir Ignatiev; Maria Pukalchik; Ivan V. Oseledets (Remote. Sens., 2021)

Generation of the NIR Spectral Band for Satellite Images with Convolutional Neural Networks. - Svetlana Illarionova; Dmitrii Shadrin; Alexey Trekin; Vladimir Ignatiev; Ivan V. Oseledets (Sensors, 2021)

Neural-Based Hierarchical Approach for Detailed Dominant Forest Species Classification by Multispectral Satellite Imagery. - Svetlana Illarionova; Alexey Trekin; Vladimir Ignatiev; Ivan V. Oseledets (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

CC-CERT: A Probabilistic Approach to Certify General Robustness of Neural Networks. - Mikhail Pautov; Nurislam Tursynbek; Marina Munkhoeva; Nikita Muravev; Aleksandr Petiushko; Ivan V. Oseledets (AAAI, 2022)

T4DT: Tensorizing Time for Learning Temporal 3D Visual Data. - Mikhail Usvyatsov; Rafael Ballester; Lina Bashaeva; Konrad Schindler; Gonzalo Ferrer 001; Ivan V. Oseledets (BMVC, 2022)

Hyperbolic Vision Transformers: Combining Improvements in Metric Learning. - Aleksandr Ermolov; Leyla Mirvakhabova; Valentin Khrulkov; Nicu Sebe; Ivan V. Oseledets (CVPR, 2022)

Survey on Efficient Training of Large Neural Networks. - Julia Gusak; Daria Cherniuk; Alena Shilova; Alexandr Katrutsa; Daniel Bershatsky; Xunyi Zhao; Lionel Eyraud-Dubois; Oleh Shliazhko; Denis Dimitrov; Ivan V. Oseledets; Olivier Beaumont (IJCAI, 2022)

Smoothed Embeddings for Certified Few-Shot Learning. - Mikhail Pautov; Olesya Kuznetsova; Nurislam Tursynbek; Aleksandr Petiushko; Ivan V. Oseledets (NeurIPS, 2022)

TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning. - Konstantin Sozykin; Andrei Chertkov; Roman Schutski; Anh-Huy Phan 001; Andrzej S. Cichocki; Ivan V. Oseledets (NeurIPS, 2022)

Geometry-Inspired Top-k Adversarial Perturbations. - Nurislam Tursynbek; Aleksandr Petiushko; Ivan V. Oseledets (WACV, 2022)

Estimation of the Canopy Height Model From Multispectral Satellite Imagery With Convolutional Neural Networks. - Svetlana Illarionova; Dmitrii Shadrin; Vladimir Ignatiev; Sergey Shayakhmetov; Alexey Trekin; Ivan V. Oseledets (IEEE Access, 2022)

XtremeAugment: Getting More From Your Data Through Combination of Image Collection and Image Augmentation. - Sergey Nesteruk; Svetlana Illarionova; Timur Akhtyamov; Dmitrii Shadrin; Andrey Somov; Mariia Pukalchik; Ivan V. Oseledets (IEEE Access, 2022)

Denoising Score Matching via Random Fourier Features. - Olga Tsymboi; Yermek Kapushev; Evgeny Burnaev; Ivan V. Oseledets (IEEE Access, 2022)

Memory-Efficient Backpropagation through Large Linear Layers. - Daniel Bershatsky; Aleksandr Mikhalev; Alexandr Katrutsa; Julia Gusak; Daniil Merkulov; Ivan V. Oseledets (CoRR, 2022)

Understanding DDPM Latent Codes Through Optimal Transport. - Valentin Khrulkov; Ivan V. Oseledets (CoRR, 2022)

Survey on Large Scale Neural Network Training. - Julia Gusak; Daria Cherniuk; Alena Shilova; Alexandr Katrutsa; Daniel Bershatsky; Xunyi Zhao; Lionel Eyraud-Dubois; Oleg Shlyazhko; Denis Dimitrov; Ivan V. Oseledets; Olivier Beaumont (CoRR, 2022)

On the Performance of Machine Learning Methods for Breakthrough Curve Prediction. - Daria Fokina; Oleg Iliev 001; Pavel Toktaliev; Ivan V. Oseledets; Felix Schindler (CoRR, 2022)

Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks. - Artyom Nikitin; Andrei Chertkov; Rafael Ballester-Ripoll; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2022)

Tensor-based Collaborative Filtering With Smooth Ratings Scale. - Nikita Marin; Elizaveta Makhneva; Maria Lysyuk; Vladimir Chernyy; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2022)

Spectral Neural Operators. - Vladimir Fanaskov; Ivan V. Oseledets (CoRR, 2022)

Tensor networks in machine learning. - Richik Sengupta; Soumik Adhikary; Ivan V. Oseledets; Jacob D. Biamonte (CoRR, 2022)

Cross Tensor Approximation for Image and Video Completion. - Salman Ahmadi-Asl; Maame Gyamfua Asante-Mensah; Andrzej Cichocki; Anh Huy Phan 001; Ivan V. Oseledets; Jun Wang 002 (CoRR, 2022)

Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI. - Semen A. Budennyy; Vladimir D. Lazarev; Nikita Zakharenko; Alexey N. Korovin; Olga Plosskaya; Denis Dimitrov; Vladimir Arkhipkin; Ivan V. Oseledets; Ivan Barsola; Ilya Egorov; Aleksandra Kosterina; Leonid Zhukov (CoRR, 2022)

Optimization of Functions Given in the Tensor Train Format. - Andrei Chertkov; Gleb V. Ryzhakov; Georgii S. Novikov; Ivan V. Oseledets (CoRR, 2022)

NAG-GS: Semi-Implicit, Accelerated and Robust Stochastic Optimizers. - Valentin Leplat; Daniil Merkulov; Aleksandr Katrutsa; Daniel Bershatsky; Ivan V. Oseledets (CoRR, 2022)

FMM-Net: neural network architecture based on the Fast Multipole Method. - Daria A. Sushnikova; Pavel Kharyuk; Ivan V. Oseledets (CoRR, 2022)

Direct optimization of BPX preconditioners. - Ivan V. Oseledets; Vladimir Fanaskov (J. Comput. Appl. Math., 2022)

Augmentation-Based Methodology for Enhancement of Trees Map Detalization on a Large Scale. - Svetlana Illarionova; Dmitrii Shadrin; Vladimir Ignatiev; Sergey Shayakhmetov; Alexey Trekin; Ivan V. Oseledets (Remote. Sens., 2022)

A Survey of Computer Vision Techniques for Forest Characterization and Carbon Monitoring Tasks. - Svetlana Illarionova; Dmitrii Shadrin; Polina Tregubova; Vladimir Ignatiev; Albert Efimov; Ivan V. Oseledets; Evgeny Burnaev (Remote. Sens., 2022)

Bayesian Aggregation Improves Traditional Single-Image Crop Classification Approaches. - Ivan Matvienko; Mikhail Gasanov; Anna Petrovskaia; Maxim A. Kuznetsov; Raghavendra B. Jana; Maria Pukalchik; Ivan V. Oseledets (Sensors, 2022)

A Single Image Deep Learning Approach to Restoration of Corrupted Landsat-7 Satellite Images. - Anna Petrovskaia; Raghavendra B. Jana; Ivan V. Oseledets (Sensors, 2022)

Automatic Differentiation for Riemannian Optimization on Low-Rank Matrix and Tensor-Train Manifolds. - Alexander Novikov 001; Maxim V. Rakhuba; Ivan V. Oseledets (SIAM J. Sci. Comput., 2022)

Quantized Tensor FEM for Multiscale Problems: Diffusion Problems in Two and Three Dimensions. - Vladimir A. Kazeev; Ivan V. Oseledets; Maxim V. Rakhuba; Christoph Schwab (Multiscale Model. Simul., 2022)

Layerwise universal adversarial attack on NLP models. - Olga Tsymboi; Danil Malaev; Andrei Petrovskii; Ivan V. Oseledets (ACL (Findings), 2023)

Understanding DDPM Latent Codes Through Optimal Transport. - Valentin Khrulkov; Gleb V. Ryzhakov; Andrei Chertkov; Ivan V. Oseledets (ICLR, 2023)

Constructive TT-representation of the tensors given as index interaction functions with applications. - Gleb V. Ryzhakov; Ivan V. Oseledets (ICLR, 2023)

General Covariance Data Augmentation for Neural PDE Solvers. - Vladimir Fanaskov; Tianchi Yu; Alexander Rudikov; Ivan V. Oseledets (ICML, 2023)

Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction. - Georgii Sergeevich Novikov; Daniel Bershatsky; Julia Gusak; Alex Shonenkov; Denis Valerievich Dimitrov; Ivan V. Oseledets (ICML, 2023)

Machine Learning Algorithms for Parameter Identification for Reactive Flow in Porous Media. - Daria Fokina; Vasiliy V. Grigoriev; Oleg Iliev 001; Ivan V. Oseledets (LSSC, 2023)

Feature-Based Pipeline for Improving Unsupervised Anomaly Segmentation on Medical Images. - Daria Frolova; Aleksandr Katrutsa; Ivan V. Oseledets (UNSURE@MICCAI, 2023)

PROTES: Probabilistic Optimization with Tensor Sampling. - Anastasia Batsheva; Andrei Chertkov; Gleb V. Ryzhakov; Ivan V. Oseledets (NeurIPS, 2023)

Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning. - Marina Munkhoeva; Ivan V. Oseledets (NeurIPS, 2023)

Efficient GPT Model Pre-training using Tensor Train Matrix Representation. - Viktoria Chekalina; Georgiy Novikov; Julia Gusak; Alexander Panchenko; Ivan V. Oseledets (PACLIC, 2023)

Fast Adaptive Cross Tubal Tensor Approximation. - Salman Ahmadi-Asl; Anh Huy Phan 001; Andrzej Cichocki; Ashish Jha; Anastasia Sozykina; Jun Wang 002; Ivan V. Oseledets (SSP, 2023)

Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations. - Evgeny Frolov; Ivan V. Oseledets (IEEE Access, 2023)

PseudoAugment: Enabling Smart Checkout Adoption for New Classes Without Human Annotation. - Sergey Nesteruk; Svetlana Illarionova; Ilya Zherebzov; Claire Traweek; Nadezhda Mikhailova; Andrey Somov; Ivan V. Oseledets (IEEE Access, 2023)

Mitigating Human and Computer Opinion Fraud via Contrastive Learning. - Yuliya Tukmacheva; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2023)

Machine learning methods for prediction of breakthrough curves in reactive porous media. - Daria Fokina; Pavel Toktaliev; Oleg Iliev 001; Ivan V. Oseledets (CoRR, 2023)

Translate your gibberish: black-box adversarial attack on machine translation systems. - Andrei Chertkov; Olga Tsymboi; Mikhail Pautov; Ivan V. Oseledets (CoRR, 2023)

TT-SDF2PC: Registration of Point Cloud and Compressed SDF Directly in the Memory-Efficient Tensor Train Domain. - Alexey I. Boyko; Anastasiia Kornilova; Rahim Tariverdizadeh; Mirfarid Musavian Ghazani; Larisa Markeeva; Ivan V. Oseledets; Gonzalo Ferrer 001 (CoRR, 2023)

Adaptive Cross Tubal Tensor Approximation. - Salman Ahmadi-Asl; Anh Huy Phan 001; Andrzej Cichocki; Anastasia Sozykina; Zaher Al Aghbari; Jun Wang 002; Ivan V. Oseledets (CoRR, 2023)

Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning. - Marina Munkhoeva; Ivan V. Oseledets (CoRR, 2023)

Efficient GPT Model Pre-training using Tensor Train Matrix Representation. - Viktoria Chekalina; Georgii S. Novikov; Julia Gusak; Ivan V. Oseledets; Alexander Panchenko (CoRR, 2023)

Robust GAN inversion. - Egor Sevriugov; Ivan V. Oseledets (CoRR, 2023)

Unsupervised evaluation of GAN sample quality: Introducing the TTJac Score. - Egor Sevriugov; Ivan V. Oseledets (CoRR, 2023)

On the structure of the Schur complement matrix for the Stokes equation. - Vladislav Pimanov; Ekaterina A. Muravleva; Ivan V. Oseledets; Oleg Iliev 001 (CoRR, 2023)

Memory-efficient particle filter recurrent neural network for object localization. - Roman Korkin; Ivan V. Oseledets; Aleksandr Katrutsa (CoRR, 2023)

Run LoRA Run: Faster and Lighter LoRA Implementations. - Daria Cherniuk; Aleksandr Mikhalev; Ivan V. Oseledets (CoRR, 2023)

TERM Model: Tensor Ring Mixture Model for Density Estimation. - Ruituo Wu; Jiani Liu 002; Ce Zhu; Anh Huy Phan 001; Ivan V. Oseledets; Yipeng Liu 001 (CoRR, 2023)

Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems. - Albert Saiapin; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2023)

Tensor Train Decomposition for Adversarial Attacks on Computer Vision Models. - Andrei Chertkov; Ivan V. Oseledets (CoRR, 2023)

Tensor Extrema Estimation Via Sampling: A New Approach for Determining Minimum/Maximum Elements. - Andrei Chertkov; Gleb V. Ryzhakov; Georgii S. Novikov; Ivan V. Oseledets (Comput. Sci. Eng., 2023)

Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction. - Aleksandr Katrutsa; Sergey V. Utyuzhnikov; Ivan V. Oseledets (J. Comput. Phys., 2023)

An event-triggered iteratively reweighted convex optimization approach to multi-period portfolio selection. - Filipp Skomorokhov; Jun Wang 002; George V. Ovchinnikov; Evgeny Burnaev; Ivan V. Oseledets (Expert Syst. Appl., 2023)

Local convergence of alternating low-rank optimization methods with overrelaxation. - Ivan V. Oseledets; Maxim V. Rakhuba; André Uschmajew (Numer. Linear Algebra Appl., 2023)

Benchmark for Building Segmentation on Up-Scaled Sentinel-2 Imagery. - Svetlana Illarionova; Dmitrii Shadrin; Islomjon Shukhratov; Ksenia Evteeva; Georgii Popandopulo; Nazar Sotiriadi; Ivan V. Oseledets; Evgeny Burnaev (Remote. Sens., 2023)

Black Box Approximation in the Tensor Train Format Initialized by ANOVA Decomposition. - Andrei Chertkov; Gleb V. Ryzhakov; Ivan V. Oseledets (SIAM J. Sci. Comput., 2023)

Fast cross tensor approximation for image and video completion. - Salman Ahmadi-Asl; Maame Gyamfua Asante-Mensah; Andrzej Cichocki; Anh-Huy Phan 001; Ivan V. Oseledets; Jun Wang 002 (Signal Process., 2023)

Your Transformer is Secretly Linear. - Anton Razzhigaev; Matvey Mikhalchuk; Elizaveta Goncharova; Nikolai Gerasimenko; Ivan V. Oseledets; Denis Dimitrov; Andrey Kuznetsov (ACL (1), 2024)

RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders. - Danil Gusak; Gleb Mezentsev; Ivan V. Oseledets; Evgeny Frolov (CIKM, 2024)

The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models. - Anton Razzhigaev; Matvey Mikhalchuk; Elizaveta Goncharova; Ivan V. Oseledets; Denis Dimitrov; Andrey Kuznetsov (EACL (Findings), 2024)

General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing. - Dmitrii Korzh; Mikhail Pautov; Olga Tsymboi; Ivan V. Oseledets (ECAI, 2024)

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers. - Viktoria Chekalina; Anna Rudenko; Gleb Mezentsev; Aleksandr Mikhalev; Alexander Panchenko; Ivan V. Oseledets (EMNLP, 2024)

Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving. - Alexander Rudikov; Vladimir Fanaskov; Ekaterina A. Muravleva; Yuri M. Laevsky; Ivan V. Oseledets (ICML, 2024)

Probabilistically Robust Watermarking of Neural Networks. - Mikhail Pautov; Nikita Bogdanov; Stanislav Pyatkin; Oleg Rogov; Ivan V. Oseledets (IJCAI, 2024)

Anatomical Positional Embeddings. - Mikhail Goncharov; Valentin Samokhin; Eugenia Soboleva; Roman Sokolov; Boris Shirokikh; Mikhail Belyaev; Anvar Kurmukov; Ivan V. Oseledets (MICCAI (10), 2024)

Self-Attentive Sequential Recommendations with Hyperbolic Representations. - Evgeny Frolov; Tatyana Matveeva; Leyla Mirvakhabova; Ivan V. Oseledets (RecSys, 2024)

Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs. - Gleb Mezentsev; Danil Gusak; Ivan V. Oseledets; Evgeny Frolov (RecSys, 2024)

Quantization of Large Language Models with an Overdetermined Basis. - Daniil Merkulov; Daria Cherniuk; Alexander Rudikov; Ivan V. Oseledets; Ekaterina A. Muravleva; Aleksandr Mikhalev; Boris Kashin (UAI, 2024)

Corrections to "Randomized Algorithms for Computation of Tucker Decomposition and Higher Order SVD (HOSVD)". - Salman Ahmadi-Asl; Stanislav Abukhovich; Maame G. Asante-Mensah; Andrzej Cichocki; Anh Huy Phan 001; Tohishisa Tanaka; Ivan V. Oseledets (IEEE Access, 2024)

Sparse and Transferable Universal Singular Vectors Attack. - Kseniia Kuvshinova; Olga Tsymboi; Ivan V. Oseledets (CoRR, 2024)

TQCompressor: improving tensor decomposition methods in neural networks via permutations. - Vadim Abronin; Aleksei Naumov; Denis Mazur; Dmitriy Bystrov; Katerina Tsarova; Artem Melnikov; Ivan V. Oseledets; Sergey Dolgov; Reuben Brasher; Michael Perelshtein (CoRR, 2024)

LoTR: Low Tensor Rank Weight Adaptation. - Daniel Bershatsky; Daria Cherniuk; Talgat Daulbaev; Aleksandr Mikhalev; Ivan V. Oseledets (CoRR, 2024)

Black-Box Approximation and Optimization with Hierarchical Tucker Decomposition. - Gleb V. Ryzhakov; Andrei Chertkov; Artem Basharin; Ivan V. Oseledets (CoRR, 2024)

Smart Flow Matching: On The Theory of Flow Matching Algorithms with Applications. - Gleb V. Ryzhakov; Svetlana Pavlova; Egor Sevriugov; Ivan V. Oseledets (CoRR, 2024)

Neural functional a posteriori error estimates. - Vladimir Fanaskov; Alexander Rudikov; Ivan V. Oseledets (CoRR, 2024)

OmniFusion Technical Report. - Elizaveta Goncharova; Anton Razzhigaev; Matvey Mikhalchuk; Maxim Kurkin; Irina Abdullaeva; Matvey Skripkin; Ivan V. Oseledets; Denis Dimitrov; Andrey Kuznetsov (CoRR, 2024)

GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation. - Andrey V. Galichin; Mikhail Pautov; Alexey Zhavoronkin; Oleg Y. Rogov; Ivan V. Oseledets (CoRR, 2024)

Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers. - Vladislav Trifonov; Alexander Rudikov; Oleg Iliev 001; Ivan V. Oseledets; Ekaterina A. Muravleva (CoRR, 2024)

Astral: training physics-informed neural networks with error majorants. - Vladimir Fanaskov; Tianchi Yu; Alexander Rudikov; Ivan V. Oseledets (CoRR, 2024)

ConDiff: A Challenging Dataset for Neural Solvers of Partial Differential Equations. - Vladislav Trifonov; Alexander Rudikov; Oleg Iliev 001; Ivan V. Oseledets; Ekaterina A. Muravleva (CoRR, 2024)

Inverted Activations. - Georgii S. Novikov; Ivan V. Oseledets (CoRR, 2024)

Fourier Spectral Physics Informed Neural Network: An Efficient and Low-Memory PINN. - Tianchi Yu; Yiming Qi; Ivan V. Oseledets; Shiyi Chen (CoRR, 2024)

Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks. - Tianchi Yu; Jingwei Qiu; Jiang Yang; Ivan V. Oseledets (CoRR, 2024)

Tensor-Train Point Cloud Compression and Efficient Approximate Nearest-Neighbor Search. - Georgii S. Novikov; Alexander Gneushev; Alexey Kadeishvili; Ivan V. Oseledets (CoRR, 2024)

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers. - Viktoria Chekalina; Anna Rudenko; Gleb Mezentsev; Alexander Mikhalev; Alexander Panchenko; Ivan V. Oseledets (CoRR, 2024)

Faster Language Models with Better Multi-Token Prediction Using Tensor Decomposition. - Artem Basharin; Andrei Chertkov; Ivan V. Oseledets (CoRR, 2024)

Integrating Geodesic Interpolation and Flow Matching for Non-Autoregressive Text Generation in Logit Space. - Egor Sevriugov; Ivan V. Oseledets (CoRR, 2024)

Quantization Aware Factorization for Deep Neural Network Compression. - Daria Cherniuk; Stanislav Abukhovich; Anh Huy Phan 001; Ivan V. Oseledets; Andrzej Cichocki; Julia Gusak (J. Artif. Intell. Res., 2024)

Multiparticle Kalman filter for object localization in symmetric environments. - Roman Korkin; Ivan V. Oseledets; Aleksandr Katrutsa (Expert Syst. Appl., 2024)

Federated privacy-preserving collaborative filtering for on-device next app prediction. - Albert Saiapin; Gleb Balitskiy; Daniel Bershatsky; Aleksandr Katrutsa; Evgeny Frolov; Alexey A. Frolov; Ivan V. Oseledets; Vitaliy Kharin (User Model. User Adapt. Interact., 2024)

On the efficient preconditioning of the Stokes equations in tight geometries. - Vladislav Pimanov; Oleg Iliev 001; Ivan V. Oseledets; Ekaterina A. Muravleva (Numer. Linear Algebra Appl., 2024)

Certification of Speaker Recognition Models to Additive Perturbations. - Dmitrii Korzh; Elvir Karimov; Mikhail Pautov; Oleg Y. Rogov; Ivan V. Oseledets (AAAI, 2025)

CLEAR: Character Unlearning in Textual and Visual Modalities. - Alexey Dontsov; Dmitrii Korzh; Alexey Zhavoronkin; Boris Mikheev; Denis Bobkov; Aibek Alanov; Oleg Rogov; Ivan V. Oseledets; Elena Tutubalina (ACL (Findings), 2025)

Associative memory and dead neurons. - Vladimir Fanaskov; Ivan V. Oseledets (ICLR, 2025)

LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers. - Anton Razzhigaev; Matvey Mikhalchuk; Temurbek Rahmatullaev; Elizaveta Goncharova; Polina Druzhinina; Ivan V. Oseledets; Andrey Kuznetsov (NAACL (Findings), 2025)

Data-driven optimal prediction with control. - Aleksandr Katrutsa; Ivan V. Oseledets; Sergey V. Utyuzhnikov (Commun. Nonlinear Sci. Numer. Simul., 2025)

Fast gradient-free activation maximization for neurons in spiking neural networks. - Nikita Pospelov; Andrei Chertkov; Maxim Beketov; Ivan V. Oseledets; Konstantin Anokhin (Neurocomputing, 2025)

GLiRA: Closed-Box Membership Inference Attack via Knowledge Distillation. - Andrey V. Galichin; Mikhail Pautov; Alexey Zhavoronkin; Oleg Y. Rogov; Ivan V. Oseledets (IEEE Trans. Inf. Forensics Secur., 2025)

Can message-passing GNN approximate triangular factorizations of sparse matrices? - Vladislav Trifonov; Ekaterina A. Muravleva; Ivan V. Oseledets (CoRR, 2025)

MaxInfo: A Training-Free Key-Frame Selection Method Using Maximum Volume for Enhanced Video Understanding. - Pengyi Li 003; Irina Abdullaeva; Alexander Gambashidze; Andrey Kuznetsov; Ivan V. Oseledets (CoRR, 2025)

Spread them Apart: Towards Robust Watermarking of Generated Content. - Mikhail Pautov; Danil Ivanov; Andrey V. Galichin; Oleg Rogov; Ivan V. Oseledets (CoRR, 2025)

Screener: Self-supervised Pathology Segmentation Model for 3D Medical Images. - Mikhail Goncharov; Eugenia Soboleva; Maria Donskova; Ivan V. Oseledets; Marina Munkhoeva; Maxim Panov (CoRR, 2025)

FLAME: Flexible LLM-Assisted Moderation Engine. - Ivan Bakulin; Ilia Kopanichuk; Iaroslav Bespalov; Nikita Radchenko; Vladimir Shaposhnikov; Dmitry V. Dylov; Ivan V. Oseledets (CoRR, 2025)

M3DA: Benchmark for Unsupervised Domain Adaptation in 3D Medical Image Segmentation. - Boris Shirokikh; Anvar Kurmukov; Maria Donskova; Valentin Samokhin; Mikhail Belyaev; Ivan V. Oseledets (CoRR, 2025)

Combining Flow Matching and Transformers for Efficient Solution of Bayesian Inverse Problems. - Daniil Sherki; Ivan V. Oseledets; Ekaterina A. Muravleva (CoRR, 2025)

Exploring specialization and sensitivity of convolutional neural networks in the context of simultaneous image augmentations. - Pavel Kharyuk; Sergey A. Matveev; Ivan V. Oseledets (CoRR, 2025)

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders. - Andrey V. Galichin; Alexey Dontsov; Polina Druzhinina; Anton Razzhigaev; Oleg Y. Rogov; Elena Tutubalina; Ivan V. Oseledets (CoRR, 2025)

On the Spatial Structure of Mixture-of-Experts in Transformers. - Daniel Bershatsky; Ivan V. Oseledets (CoRR, 2025)

NNTile: a machine learning framework capable of training extremely large GPT language models on a single node. - Aleksandr Mikhalev; Aleksandr Katrutsa; Konstantin Sozykin; Ivan V. Oseledets (CoRR, 2025)

A case study of spatiotemporal forecasting techniques for weather forecasting. - Shakir Showkat Sofi; Ivan V. Oseledets (GeoInformatica, 2025)

Binding threshold units with artificial oscillatory neurons. - Vladimir Fanaskov; Ivan V. Oseledets (CoRR, 2025)

High-dimensional Optimization with Low Rank Tensor Sampling and Local Search. - Konstantin Sozykin; Andrei Chertkov; Anh Huy Phan 001; Ivan V. Oseledets; Gleb V. Ryzhakov (CoRR, 2025)

Locally Subspace-Informed Neural Operators for Efficient Multiscale PDE Solving. - Alexander Rudikov; Vladimir Fanaskov; Sergei Stepanov; Buzheng Shan; Ekaterina A. Muravleva; Yalchin Efendiev; Ivan V. Oseledets (CoRR, 2025)

Exploring the Latent Capacity of LLMs for One-Step Text Generation. - Gleb Mezentsev; Ivan V. Oseledets (CoRR, 2025)

One Task Vector is not Enough: A Large-Scale Study for In-Context Learning. - Pavel Tikhonov; Ivan V. Oseledets; Elena Tutubalina (CoRR, 2025)

Curse of Slicing: Why Sliced Mutual Information is a Deceptive Measure of Statistical Dependence. - Alexander Semenenko; Ivan Butakov; Alexey A. Frolov; Ivan V. Oseledets (CoRR, 2025)

Geological Field Restoration through the Lens of Image Inpainting. - Vladislav Trifonov; Ivan V. Oseledets; Ekaterina A. Muravleva (CoRR, 2025)

Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts. - Danil Sivtsov; Ivan Rodkin; Gleb Kuzmin; Yuri Kuratov; Ivan V. Oseledets (CoRR, 2025)

Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models. - Pengyi Li 003; Matvey Skripkin; Alexander Zubrey; Andrey Kuznetsov; Ivan V. Oseledets (CoRR, 2025)

Geopolitical biases in LLMs: what are the "good" and the "bad" countries according to contemporary language models. - Mikhail Salnikov; Dmitrii Korzh; Ivan Lazichny; Elvir Karimov; Artyom Iudin; Ivan V. Oseledets; Oleg Y. Rogov; Natalia V. Loukachevitch; Alexander Panchenko; Elena Tutubalina (CoRR, 2025)

Listener-Rewarded Thinking in VLMs for Image Preferences. - Alexander Gambashidze; Pengyi Li 003; Matvey Skripkin; Andrey V. Galichin; Anton Gusarov; Konstantin Sobolev; Andrey Kuznetsov; Ivan V. Oseledets (CoRR, 2025)

Quasi-Random Physics-informed Neural Networks. - Tianchi Yu; Ivan V. Oseledets (CoRR, 2025)

Speech-to-LaTeX: New Models and Datasets for Converting Spoken Equations and Sentences. - Dmitrii Korzh; Dmitrii Tarasov; Artyom Iudin; Elvir Karimov; Matvey Skripkin; Nikita Kuzmin; Andrey Kuznetsov; Oleg Y. Rogov; Ivan V. Oseledets (CoRR, 2025)

Cluster Topology-Driven Placement of Experts Reduces Network Traffic in MoE Inference. - Danil Sivtsov; Aleksandr Katrutsa; Ivan V. Oseledets (CoRR, 2025)