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Probabilistic numerical methods for partial differential equations: Elements of analysis · Study

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ChapterProbabilistic numerical methods for partial differential equations: Elements of analysis

Denis Talay1996

Chapter1996

Probabilistic numerical methods for partial differential equations: Elements of analysis

70 citations·0/0 files stored·Lecture notes in mathematics

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Probabilistic and Robust Engineering Design Numerical methods for differential equations Gaussian Processes and Bayesian Inference

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References

2008Stochastic differential equations and applications 2005Stochastic Integration and Differential Equations 1983Stochastic Differential Equations and Diffusion Processes 2006The Malliavin Calculus and Related Topics 1995The Malliavin Calculus and Related Topics 1976Stochastic Differential Equations and Applications 1990Stochastic Integration and Differential Equations 1996The law of the Euler scheme for stochastic differential equations

Cited by

2010Weak approximation of stochastic partial differential equations: the nonlinear case 2007An Introduction to (Stochastic) Calculus with Respect to Fractional Brownian Motion 2005Euler scheme and tempered distributions 2012Counterparty Risk Valuation: A Marked Branching Diffusion Approach 2002Rate of convergence of a particle method to the solution of the McKean--Vlasov equation 2011Convergence of the Stochastic Euler Scheme for Locally Lipschitz Coefficients

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Details

Year1996

Typechapter

Published1996-01-01

VenueLecture notes in mathematics

ISSN-L0075-8434

Languageen

Citations70

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1007/bfb0093180

openalex_workW1548626814

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2003A stochastic particle method with random weights for the computation of statistical solutions of McKean-Vlasov equations

2005Some stochastic particle methods for nonlinear parabolic PDEs