Sergey V. Dolgov

According to our database, Sergey V. Dolgov authored at least 44 papers between 2012 and 2024.

Collaborative distances:

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

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., February, 2024

Tensor product approach to modelling epidemics on networks.

Sergey Dolgov, Dmitry V. Savostyanov

Appl. Math. Comput., January, 2024

TQCompressor: improving tensor decomposition methods in neural networks via permutations.

V. Abronin, A. Naumov, D. Mazur, D. Bystrov, K. Tsarova, Artem Melnikov, Ivan V. Oseledets, Sergey Dolgov, R. Brasher, Michael Perelshtein

CoRR, 2024

Tensor product algorithms for inference of contact network from epidemiological data.

Sergey Dolgov, Dmitry V. Savostyanov

CoRR, 2024

2023

Data-Driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations.

Sergey Dolgov, Dante Kalise, Luca Saluzzi

SIAM J. Sci. Comput., October, 2023

TTRISK: Tensor train decomposition algorithm for risk averse optimization.

Harbir Antil, Sergey Dolgov, Akwum Onwunta

Numer. Linear Algebra Appl., May, 2023

Efficient Structure-preserving Support Tensor Train Machine.

Kirandeep Kour, Sergey Dolgov, Martin Stoll, Peter Benner

J. Mach. Learn. Res., 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

Statistical Proper Orthogonal Decomposition for model reduction in feedback control.

Sergey Dolgov, Dante Kalise, Luca Saluzzi

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

Self-reinforced polynomial approximation methods for concentrated probability densities.

Tiangang Cui, Sergey Dolgov, Olivier Zahm

CoRR, 2023

A weighted subspace exponential kernel for support tensor machines.

Kirandeep Kour, Sergey Dolgov, Peter Benner, Martin Stoll, Max Pfeffer

CoRR, 2023

State-constrained Optimization Problems under Uncertainty: A Tensor Train Approach.

Harbir Antil, Sergey Dolgov, Akwum Onwunta

CoRR, 2023

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, March, 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

Deep Composition of Tensor-Trains Using Squared Inverse Rosenblatt Transports.

Tiangang Cui, Sergey Dolgov

Found. Comput. Math., 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

Undersampling Raster Scans in Spectromicroscopy for reduced dose and faster measurements.

Oliver Townsend, Silvia Gazzola, Sergey Dolgov, Paul Quinn

CoRR, 2022

Optimizing semilinear representations for State-dependent Riccati Equation-based feedback control.

Sergey Dolgov, Dante Kalise, Luca Saluzzi

CoRR, 2022

2021

Functional Tucker Approximation Using Chebyshev Interpolation.

Sergey Dolgov, Daniel Kressner, Christoph Strössner

SIAM J. Sci. Comput., 2021

Tensor Decomposition Methods for High-dimensional Hamilton-Jacobi-Bellman Equations.

Sergey Dolgov, Dante Kalise, Karl Kunisch

SIAM J. Sci. Comput., 2021

Conditional Deep Inverse Rosenblatt Transports.

Tiangang Cui, Sergey Dolgov, Olivier Zahm

CoRR, 2021

2020

A Low-Rank Tensor Method for PDE-Constrained Optimization with Isogeometric Analysis.

Alexandra Bünger, Sergey Dolgov, Martin Stoll

SIAM J. Sci. Comput., 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

Parallel cross interpolation for high-precision calculation of high-dimensional integrals.

Sergey Dolgov, Dmitry V. Savostyanov

Comput. Phys. Commun., 2020

2019

Preconditioners and Tensor Product Solvers for Optimal Control Problems from Chemotaxis.

Sergey Dolgov, John W. Pearson

SIAM J. Sci. Comput., 2019

A Hybrid Alternating Least Squares-TT-Cross Algorithm for Parametric PDEs.

Sergey Dolgov, Robert Scheichl

SIAM/ASA J. Uncertain. Quantification, 2019

Solving differential Riccati equations: A nonlinear space-time method using tensor trains.

Tobias Breiten, Sergey Dolgov, Martin Stoll

CoRR, 2019

A Tensor Decomposition Approach for High-Dimensional Hamilton-Jacobi-Bellman Equations.

Sergey Dolgov, Dante Kalise, Karl Kunisch

CoRR, 2019

A Tensor Decomposition Algorithm for Large ODEs with Conservation Laws.

Sergey V. Dolgov

Comput. Methods Appl. Math., 2019

2018

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

2017

Low-Rank Solution to an Optimization Problem Constrained by the Navier-Stokes Equations.

Sergey Dolgov, Martin Stoll

SIAM J. Sci. Comput., 2017

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

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 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

2015

Simultaneous state-time approximation of the chemical master equation using tensor product formats.

Sergey Dolgov, Boris N. Khoromskij

Numer. Linear Algebra Appl., 2015

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

2014

Alternating Minimal Energy Methods for Linear Systems in Higher Dimensions.

Sergey Dolgov, Dmitry V. Savostyanov

SIAM J. Sci. Comput., 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

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

2013

Two-Level QTT-Tucker Format for Optimized Tensor Calculus.

Sergey Dolgov, Boris N. Khoromskij

SIAM J. Matrix Anal. Appl., 2013

Corrected One-Site Density Matrix Renormalization Group and Alternating Minimal Energy Algorithm.

Sergey Dolgov, Dmitry V. Savostyanov

Proceedings of the Numerical Mathematics and Advanced Applications - ENUMATH 2013, 2013

2012

Solution of Linear Systems and Matrix Inversion in the TT-Format.

Ivan V. Oseledets, Sergey V. Dolgov

SIAM J. Sci. Comput., 2012

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