3 citations · 6 across the 3 of their papers we have counts for
8 papers
An energy-based deep splitting method for the nonlinear filtering problem
Kasper Bågmark, Adam Andersson, Stig Larsson
The purpose of this paper is to explore the use of deep learning for the solution of the nonlinear filtering problem. This is achieved by solving the Zakai equation by a deep split…
Convergence of a robust deep FBSDE method for stochastic control
Kristoffer Andersson, Adam Andersson, Cornelis W. Oosterlee
In this paper, we propose a deep learning based numerical scheme for strongly coupled FBSDEs, stemming from stochastic control. It is a modification of the deep BSDE method in whic…
Finite element approximation of Lyapunov equations related to parabolic stochastic PDEs
Adam Andersson, Annika Lang, Andreas Petersson +1
A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicat…
Malliavin regularity and weak approximation of semilinear SPDE with Lévy noise
Adam Andersson, Felix Lindner
We investigate the weak order of convergence for space-time discrete approximations of semilinear parabolic stochastic evolution equations driven by additive square-integrable Lévy…
Poisson Malliavin calculus in Hilbert space with an application to SPDE
Adam Andersson, Felix Lindner
In this paper we introduce a Hilbert space-valued Malliavin calculus for Poisson random measures. It is solely based on elementary principles from the theory of point processes and…
Regularity properties for solutions of infinite dimensional Kolmogorov equations in Hilbert spaces
Adam Andersson, Mario Hefter, Arnulf Jentzen +1
In this article we establish regularity properties for solutions of infinite dimensional Kolmogorov equations. We prove that if the nonlinear drift coefficients, the nonlinear diff…