[HTML][HTML] Sparse high-dimensional FFT based on rank-1 lattice sampling
In this paper, we suggest approximate algorithms for the reconstruction of sparse high-
dimensional trigonometric polynomials, where the support in frequency domain is unknown …
dimensional trigonometric polynomials, where the support in frequency domain is unknown …
[HTML][HTML] Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats
In this article, we describe an efficient approximation of the stochastic Galerkin matrix which
stems from a stationary diffusion equation. The uncertain permeability coefficient is assumed …
stems from a stationary diffusion equation. The uncertain permeability coefficient is assumed …
Adaptive near-optimal rank tensor approximation for high-dimensional operator equations
We consider a framework for the construction of iterative schemes for operator equations
that combine low-rank approximation in tensor formats and adaptive approximation in a …
that combine low-rank approximation in tensor formats and adaptive approximation in a …
A primal–dual algorithm for BSDEs
C Bender, N Schweizer, J Zhuo - Mathematical Finance, 2017 - Wiley Online Library
We generalize the primal–dual methodology, which is popular in the pricing of early‐
exercise options, to a backward dynamic programming equation associated with time …
exercise options, to a backward dynamic programming equation associated with time …
Tree adaptive approximation in the hierarchical tensor format
J Ballani, L Grasedyck - SIAM journal on scientific computing, 2014 - SIAM
The hierarchical tensor format allows for the low-parametric representation of tensors even
in high dimensions d. The efficiency of this representation strongly relies on an appropriate …
in high dimensions d. The efficiency of this representation strongly relies on an appropriate …
Error bound for piecewise deterministic processes modeling stochastic reaction systems
T Jahnke, M Kreim - Multiscale Modeling & Simulation, 2012 - SIAM
Biological processes involving the random interaction of d species with integer particle
numbers are often modeled by a Markov jump process on N_0^d. Realizations of this …
numbers are often modeled by a Markov jump process on N_0^d. Realizations of this …
On the convergence of the stochastic Galerkin method for random elliptic partial differential equations∗
A Mugler, HJ Starkloff - ESAIM: Mathematical Modelling and …, 2013 - cambridge.org
In this article we consider elliptic partial differential equations with random coefficients
and/or random forcing terms. In the current treatment of such problems by stochastic …
and/or random forcing terms. In the current treatment of such problems by stochastic …
Weak convergence of finite element approximations of linear stochastic evolution equations with additive Lévy noise
We present an abstract framework to study weak convergence of numerical approximations
of linear stochastic partial differential equations driven by additive Lévy noise. We first derive …
of linear stochastic partial differential equations driven by additive Lévy noise. We first derive …
On the -regularity and Besov smoothness of stochastic parabolic equations on bounded Lipschitz domains
P Cioica, KH Kim, K Lee, F Lindner - 2013 - projecteuclid.org
We investigate the regularity of linear stochastic parabolic equations with zero Dirichlet
boundary condition on bounded Lipschitz domains O⊂R^d with both theoretical and …
boundary condition on bounded Lipschitz domains O⊂R^d with both theoretical and …
Numerical methods for Kohn–Sham models: Discretization, algorithms, and error analysis
Numerical Methods for Kohn–Sham Models: Discretization, Algorithms, and Error Analysis |
SpringerLink Skip to main content Advertisement SpringerLink Account Menu Find a journal …
SpringerLink Skip to main content Advertisement SpringerLink Account Menu Find a journal …