Projects per year
Personal profile
Research interests
Numerical analysis, linear and multilinear algebra, matrix and tensor analysis, fast algorithms, tensor product formats, dynamical problems, stochastic models
Education/Academic qualification
Mathematics, Doctor rerum naturalium, University of Leipzig
30 Jun 2011 → 20 Aug 2014
Fingerprint Dive into the research topics where Sergey Dolgov is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 5 Similar Profiles
Tensors
Engineering & Materials Science
Tensor Product
Mathematics
Tensor Decomposition
Mathematics
Tensor
Mathematics
High-dimensional
Mathematics
Model Order Reduction
Mathematics
Minimal Energy
Mathematics
Chemotaxis
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Projects 2016 2018
- 1 Finished
Tensor product numerical methods for high-dimensional problems in probability and quantum calculations
1/01/16 → 31/12/18
Project: Research council
Research Output 2014 2019
A hybrid Alternating Least Squares - TT Cross algorithm for parametric PDEs
Dolgov, S. & Scheichl, R., 2019, In : SIAM/ASA Journal on Uncertainty Quantification. 7, 1, p. 260-291 28 p.Research output: Contribution to journal › Article
Open Access
File
Tensors
Maximum entropy methods
Probability density function
Mathematical operators
Decomposition
1
Citation
(Scopus)
A Tensor Decomposition Algorithm for Large ODEs with Conservation Laws
Dolgov, S. V., 11 Sep 2018, In : Computational Methods in Applied Mathematics.Research output: Contribution to journal › Article
Open Access
Tensor Decomposition
Decomposition Algorithm
Conservation Laws
Tensors
Conservation
Direct tensor-product solution of one-dimensional elliptic equations with parameter-dependent coefficients
Dolgov, S. V., Kazeev, V. A. & Khoromskij, B. N., 1 Mar 2018, In : Mathematics and Computers in Simulation. 145, p. 136-155 20 p.Research output: Contribution to journal › Article
Direct Product
Elliptic Equations
Tensor Product
Tensors
Tensor
6
Citations
(Scopus)
Fast iterative solution of the Bethe–Salpeter eigenvalue problem using low-rank and QTT tensor approximation
Benner, P., Dolgov, S., Khoromskaia, V. & Khoromskij, B. N., 1 Apr 2017, In : Journal of Computational Physics. 334, p. 221-239 19 p.Research output: Contribution to journal › Article
Open Access
File
iterative solution
Bethe-Salpeter equation
Tensors
eigenvalues
tensors
Low-rank solution to an optimization problem constrained by the Navier-Stokes equations
Dolgov, S. & Stoll, M., 2017, In : SIAM Journal on Scientific Computing. 39, 1, p. A255-A280Research output: Contribution to journal › Article
Open Access
File
Model Order Reduction
Constrained Optimization Problem
Navier Stokes equations
Navier-Stokes Equations
PDE-constrained Optimization