Tensor product numerical methods for high-dimensional problems in probability and quantum calculations

Dolgov, Sergey (PI)

Department of Mathematical Sciences

Project: Research council

Description

Postdoctoral EPSRC Fellowship

Status	Finished
Effective start/end date	1/01/16 → 31/12/18

Access Project

http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M019004/1

11 Article

DEEP IMPORTANCE SAMPLING USING TENSOR TRAINS WITH APPLICATION TO A PRIORI AND A POSTERIORI RARE EVENTS
Cui, T., Dolgov, S. & Scheichl, R., 29 Feb 2024, In: SIAM Journal on Scientific Computing. 46, 1, p. C1-C29
Research output: Contribution to journal › Article › peer-review

Open Access
143 Downloads (Pure)
Deep Composition of Tensor Trains using Squared Inverse Rosenblatt Transports
Cui, T. & Dolgov, S., 21 Sept 2021, In: Foundations of Computational Mathematics. 47 p.
Research output: Contribution to journal › Article

Open Access
11 Citations (SciVal)
Tensor decomposition methods for high-dimensional Hamilton-Jacobi-Bellman equations
Dolgov, S., Kalise, D. & Kunisch, K. K., 31 May 2021, In: SIAM Journal on Scientific Computing. 43, 3, p. A1625-A1650 26 p.
Research output: Contribution to journal › Article › peer-review

Open Access
54 Citations (SciVal)