S
Stig Larsson
Researcher at Chalmers University of Technology
Publications - 107
Citations - 3916
Stig Larsson is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Finite element method & Discretization. The author has an hindex of 30, co-authored 105 publications receiving 3417 citations. Previous affiliations of Stig Larsson include University of Gothenburg & ETH Zurich.
Papers
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Introduction to stochastic partial differential equations
Mihály Kovács,Stig Larsson +1 more
TL;DR: In this paper, the Hilbert space-valued Wiener process and the corresponding stochastic integral of Ito type were introduced and used together with semigroup theory to obtain existence and uniqueness of weak solutions of linear and semilinear stochiastic evolution problems in Hilbert space.
Book
Partial Differential Equations with Numerical Methods
Stig Larsson,Vidar Thomée +1 more
TL;DR: A Two-Point Boundary Value Problem with Finite Difference Methods for Elliptic Equations and Finite Element methods for Hyperbolic Equations.
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Error estimates with smooth and nonsmooth data for a finite element method for the Cahn-Hilliard equation
Charles M. Elliott,Stig Larsson +1 more
TL;DR: In this article, a finite element method for the Cahn-Hilliard equation (a semilinear parabolic equation of fourth order) is analyzed, both in a spatially semidiscrete case and in a completely discrete case based on the backward Euler method.
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Numerical solution of parabolic integro-differential equations by the discontinuous Galerkin method
TL;DR: The analysis presented allows variable time steps which, as will be shown, call then efficiently be selected to match singularities in the solution induced by singularity in the kernel of the memory term or by nonsmooth initial data.
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Posterior Contraction Rates for the Bayesian Approach to Linear Ill-Posed Inverse Problems
TL;DR: In this paper, a Bayesian nonparametric approach to a family of linear inverse problems in a separable Hilbert space setting with Gaussian noise is considered, and a method of identifying the posterior using its precision operator is presented, which enables to use partial differential equations (PDE) methodology to obtain rates of contraction of the posterior distribution to a Dirac measure centered on the true solution.