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)

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

Corrected One-Site Density Matrix Renormalization Group and Alternating Minimal Energy Algorithm. - Sergey Dolgov; Dmitry V. Savostyanov (ENUMATH, 2013)

Two-Level QTT-Tucker Format for Optimized Tensor Calculus. - Sergey Dolgov; Boris N. Khoromskij (SIAM J. Matrix Anal. Appl., 2013)

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)

Low-rank approximation in the numerical modeling of the Farley-Buneman instability in ionospheric plasma. - Sergey V. Dolgov; Alexander P. Smirnov; E. E. Tyrtyshnikov (J. Comput. Phys., 2014)

Alternating Minimal Energy Methods for Linear Systems in Higher Dimensions. - Sergey Dolgov; Dmitry V. Savostyanov (SIAM J. Sci. Comput., 2014)

Polynomial Chaos Expansion of Random Coefficients and the Solution of Stochastic Partial Differential Equations in the Tensor Train Format. - Sergey Dolgov; Boris N. Khoromskij; Alexander Litvinenko; Hermann G. Matthies (SIAM/ASA J. Uncertain. Quantification, 2015)

Simultaneous state-time approximation of the chemical master equation using tensor product formats. - Sergey Dolgov; Boris N. Khoromskij (Numer. Linear Algebra Appl., 2015)

Fast tensor product solvers for optimization problems with fractional differential equations as constraints. - Sergey Dolgov; John W. Pearson; Dmitry V. Savostyanov; Martin Stoll (Appl. Math. Comput., 2016)

Erratum: Two-Level QTT-Tucker Format for Optimized Tensor Calculus. - Simon Etter; Sergey Dolgov; Boris N. Khoromskij (SIAM J. Matrix Anal. Appl., 2016)

Fast iterative solution of the Bethe-Salpeter eigenvalue problem using low-rank and QTT tensor approximation. - Peter Benner; Sergey Dolgov; Venera Khoromskaia; Boris N. Khoromskij (J. Comput. Phys., 2017)

Low-Rank Solution to an Optimization Problem Constrained by the Navier-Stokes Equations. - Sergey Dolgov; Martin Stoll (SIAM J. Sci. Comput., 2017)

Direct tensor-product solution of one-dimensional elliptic equations with parameter-dependent coefficients. - Sergey Dolgov; Vladimir A. Kazeev; Boris N. Khoromskij (Math. Comput. Simul., 2018)

A Tensor Decomposition Algorithm for Large ODEs with Conservation Laws. - Sergey V. Dolgov (Comput. Methods Appl. Math., 2019)

A Tensor Decomposition Approach for High-Dimensional Hamilton-Jacobi-Bellman Equations. - Sergey Dolgov; Dante Kalise; Karl Kunisch (CoRR, 2019)

Solving differential Riccati equations: A nonlinear space-time method using tensor trains. - Tobias Breiten; Sergey Dolgov; Martin Stoll (CoRR, 2019)

A Hybrid Alternating Least Squares-TT-Cross Algorithm for Parametric PDEs. - Sergey Dolgov; Robert Scheichl (SIAM/ASA J. Uncertain. Quantification, 2019)

Preconditioners and Tensor Product Solvers for Optimal Control Problems from Chemotaxis. - Sergey Dolgov; John W. Pearson (SIAM J. Sci. Comput., 2019)

Parallel cross interpolation for high-precision calculation of high-dimensional integrals. - Sergey Dolgov; Dmitry V. Savostyanov (Comput. Phys. Commun., 2020)

Approximation and sampling of multivariate probability distributions in the tensor train decomposition. - Sergey Dolgov; Karim Anaya-Izquierdo; Colin Fox; Robert Scheichl (Stat. Comput., 2020)

A Low-Rank Tensor Method for PDE-Constrained Optimization with Isogeometric Analysis. - Alexandra Bünger; Sergey Dolgov; Martin Stoll (SIAM J. Sci. Comput., 2020)

Conditional Deep Inverse Rosenblatt Transports. - Tiangang Cui; Sergey Dolgov; Olivier Zahm (CoRR, 2021)

Tensor Decomposition Methods for High-dimensional Hamilton-Jacobi-Bellman Equations. - Sergey Dolgov; Dante Kalise; Karl Kunisch (SIAM J. Sci. Comput., 2021)

Functional Tucker Approximation Using Chebyshev Interpolation. - Sergey Dolgov; Daniel Kressner; Christoph Strössner (SIAM J. Sci. Comput., 2021)

Optimizing semilinear representations for State-dependent Riccati Equation-based feedback control. - Sergey Dolgov; Dante Kalise; Luca Saluzzi (CoRR, 2022)

Undersampling Raster Scans in Spectromicroscopy for reduced dose and faster measurements. - Oliver Townsend; Silvia Gazzola; Sergey Dolgov; Paul Quinn (CoRR, 2022)

Deep importance sampling using tensor-trains with application to a priori and a posteriori rare event estimation. - Tiangang Cui; Sergey Dolgov; Robert Scheichl (CoRR, 2022)

Deep Composition of Tensor-Trains Using Squared Inverse Rosenblatt Transports. - Tiangang Cui; Sergey Dolgov (Found. Comput. Math., 2022)

A quantum-inspired approach to exploit turbulence structures. - Nikita Gourianov; Michael Lubasch; Sergey Dolgov; Quincy Y. van den Berg; Hessam Babaee; Peyman Givi; Martin Kiffner; Dieter Jaksch (Nat. Comput. Sci., 2022)

Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format. - Paul B. Rohrbach; Sergey Dolgov; Lars Grasedyck; Robert Scheichl (SIAM/ASA J. Uncertain. Quantification, 2022)

State-constrained Optimization Problems under Uncertainty: A Tensor Train Approach. - Harbir Antil; Sergey Dolgov; Akwum Onwunta (CoRR, 2023)

A weighted subspace exponential kernel for support tensor machines. - Kirandeep Kour; Sergey Dolgov; Peter Benner; Martin Stoll; Max Pfeffer (CoRR, 2023)

Self-reinforced polynomial approximation methods for concentrated probability densities. - Tiangang Cui; Sergey Dolgov; Olivier Zahm (CoRR, 2023)

Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method. - Egor Kornev; Sergey Dolgov; Karan Pinto; Markus Pflitsch; Michael Perelshtein; Artem Melnikov (CoRR, 2023)

Statistical Proper Orthogonal Decomposition for model reduction in feedback control. - Sergey Dolgov; Dante Kalise; Luca Saluzzi (CoRR, 2023)

Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction. - Tiangang Cui; Sergey Dolgov; Olivier Zahm (J. Comput. Phys., 2023)

Efficient Structure-preserving Support Tensor Train Machine. - Kirandeep Kour; Sergey Dolgov; Martin Stoll; Peter Benner (J. Mach. Learn. Res., 2023)

TTRISK: Tensor train decomposition algorithm for risk averse optimization. - Harbir Antil; Sergey Dolgov; Akwum Onwunta (Numer. Linear Algebra Appl., 2023)

Data-Driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations. - Sergey Dolgov; Dante Kalise; Luca Saluzzi (SIAM J. Sci. Comput., 2023)

TQCompressor: Improving Tensor Decomposition Methods in Neural Networks Via Permutations. - Vadim Abronin; Aleksei Naumov; Denis Mazur; Dmitriy Bystrov; Katerina Tsarova; Artem Melnikov; Sergey Dolgov; Reuben Brasher; Michael Perelshtein (MIPR, 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)

Tensor train solution to uncertain optimization problems with shared sparsity penalty. - Harbir Antil; Sergey Dolgov; Akwum Onwunta (CoRR, 2024)

Tensor product approach to modelling epidemics on networks. - Sergey Dolgov; Dmitry V. Savostyanov (Appl. Math. Comput., 2024)

Deep Importance Sampling Using Tensor Trains with Application to a Priori and a Posteriori Rare Events. - Tiangang Cui; Sergey Dolgov; Robert Scheichl (SIAM J. Sci. Comput., 2024)

Tensor product algorithms for inference of contact network from epidemiological data. - Sergey Dolgov; Dmitry V. Savostyanov (BMC Bioinform., 2024)

Smoothed Moreau-Yosida Tensor-Train Approximation of State-Constrained Optimization Problems Under Uncertainty. - Harbir Antil; Sergey Dolgov; Akwum Onwunta (Numer. Linear Algebra Appl., 2025)

Tensor cross interpolation for global discrete optimization with application to Bayesian network inference. - Sergey Dolgov; Dmitry V. Savostyanov (CoRR, 2025)

Alternating steepest descent methods for tensor completion with applications to spectromicroscopy. - Oliver Townsend; Sergey Dolgov; Silvia Gazzola; Misha Elena Kilmer (CoRR, 2025)