Stable Rank-Adaptive Dynamically Orthogonal Runge–Kutta Schemes
We develop two new sets of stable, rank-adaptive Dynamically Orthogonal Runge-Kutta (DORK) schemes that capture the high-order curvature of the nonlinear low-rank manifold. The DORK schemes asymptotically approximate the truncated singular value decomposition at a greatly reduced cost while preservi...
Main Authors: | Charous, Aaron, Lermusiaux, Pierre F. J. |
---|---|
Format: | Article |
Language: | English |
Published: |
Society for Industrial & Applied Mathematics (SIAM)
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/1721.1/153761 |
Similar Items
-
Deep reinforcement learning for adaptive mesh refinement
by: Foucart, Corbin, et al.
Published: (2024) -
Stochastic Runge-Kutta method for stochastic delay differential equations
by: Norhayati, Rosli
Published: (2012) -
Stochastic Runge-Kutta method for stochastic delay differential equations
by: Rosli, Norhayati
Published: (2012) -
2-stage Stochastic Runge-Kutta for Stochastic Delay Differential Equations
by: Norhayati, Rosli, et al.
Published: (2014) -
Fifth-stage stochastic runge-kutta method for stochastic differential equations
by: Noor Amalina Nisa, Ariffin
Published: (2018)