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Inverse problems: A Bayesian perspective
- A. Stuart
- MathematicsActa Numerica
- 1 May 2010
TLDR
Multiscale Methods: Averaging and Homogenization
- G. Pavliotis, A. Stuart
- Mathematics
- 19 February 2008
TLDR
MCMC Methods for Functions: ModifyingOld Algorithms to Make Them Faster
- S. Cotter, G. Roberts, A. Stuart, D. White
- Computer Science
- 3 February 2012
TLDR
Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise
- Jonathan C. Mattingly, A. Stuart, D. Higham
- Mathematics
- 1 October 2002
The Bayesian Approach to Inverse Problems
These lecture notes highlight the mathematical and computational structure relating to the formulation of, and development of algorithms for, the Bayesian
approach to inverse problems in…
A First Course in Continuum Mechanics
- O. Gonzalez, A. Stuart
- Physics
- 18 February 2008
TLDR
Optimal tuning of the hybrid Monte Carlo algorithm
- A. Beskos, N. Pillai, G. Roberts, J. M. Sanz-Serna, A. Stuart
- Computer Science
- 25 January 2010
TLDR
Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
TLDR
Dynamical Systems And Numerical Analysis
- A. Stuart, A. R. Humphries
- Mathematics
- 1996
This book unites the study of dynamical systems and numerical solution of differential equations. The first three chapters contain the elements of the theory of dynamical systems and the numerical…
Ensemble Kalman methods for inverse problems
- M. Iglesias, K. Law, A. Stuart
- Mathematics
- 12 September 2012
TLDR
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