39 citations · 83 across the 36 of their papers we have counts for
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Strong error analysis of a stochastic exponential integrator for SPDEs driven by fractional Brownian motion with H<1/2
Antoine Tambue, Aurelien Junior Noupelah, Louis Aime Fono
Fractional Brownian motion provides a useful framework for modeling random phenomena with anti-persistent temporal correlations that arise in applications such as anomalous diffusi…
A Range-Deflated Stochastic Lanczos Quadrature Method for Large-Scale Log-Determinant Estimation
Verlon Roel Mbingui, Antoine Tambue, Issa Karambal
Estimating the logarithm of the determinant of large sparse symmetric positive definite matrices is an important problem in numerical linear algebra, machine learning, Gaussian pro…
Pathwise convergence of a linearization scheme for stochastic differential-algebraic equations under the local Lipschitz coefficients
Guy Tsafack, Antoine Tambue
The paper deals with the numerical treatment of index-1 stochastic differential-algebraic equations (SDAEs) with nonlinear coefficients that satisfy the local Lipschitz and the Kha…
Novel technique based on Léja Points Approximation for Log-determinant Estimation of Large matrices
Verlon Roel Mbingui, Antoine Tambue, Issa Karambal
The computation of the Log-determinant of large, sparse, symmetric positive definite (SPD) matrices is essential in many scientific computational fields such as numerical linear al…
Strong convergence of a semi tamed scheme for stochastic differential algebraic equation under non-global Lipschitz coefficients
Guy Tsafack, Antoine Tambue
We are investigating the first strong convergence analysis of a numerical method for stochastic differential algebraic equations (SDAEs) under a non-global Lipschitz setting. It is…
Pathwise convergence of a novel numerical scheme based on semi-implicit method for stochastic differential-algebraic equations with non-global Lipschitz coefficients
Guy Tsafack, Antoine Tambue
This paper delves into the well-posedness and the numerical approximation of non-autonomous stochastic differential algebraic equations (SDAEs) with nonlinear local Lipschitz coeff…
Strong convergence of some Magnus-type schemes for the finite element discretization of non-autonomous parabolic SPDEs driven by additive fractional Brownian motion and Poisson random measure
Aurelien Junior Noupelah, Jean Daniel Mukam, Antoine Tambue
The aim of this work is to provide the strong convergence results of numerical approximations of a general second order non-autonomous semilinear stochastic partial differential eq…
Strong convergence of an fractional exponential integrator scheme for the finite element discretization of time-fractional SPDE driven by standard and fractional Brownian motions
Aurelien Junior Noupelah, Antoine Tambue, Jean Louis Woukeng
The aim of this work is to provide the first strong convergence result of numerical approximation of a general time-fractional second order stochastic partial differential equation…
A novel high dimensional fitted scheme for stochastic optimal control problems
Christelle Dleuna Nyoumbi, Antoine Tambue
Stochastic optimal principle leads to the resolution of a partial differential equation (PDE), namely the Hamilton-Jacobi-Bellman (HJB) equation. In general, this equation cannot b…
Strong convergence rates of an exponential integrator and finite elements method for time-fractional SPDEs driven by Gaussian and non-Gaussian noises
Aurelien Junior Noupelah, Antoine Tambue
In this work, we provide the first strong convergence result of numerical approximation of a general second order semilinear stochastic fractional order evolution equation involvin…
A fitted finite volume method for stochastic optimal control Problems
Christelle Dleuna Nyoumbi, Antoine Tambue
In this article, we provide a numerical method based on fitted finite volume method to approximate the Hamilton-Jacobi-Bellman (HJB) equation coming from stochastic optimal control…
Optimal error estimate of the finite element approximation of second order semilinear non-autonomous parabolic PDEs
Antoine Tambue, Jean Daniel Mukam
In this work, we investigate the numerical approximation of the second order non-autonomous semilnear parabolic partial differential equation (PDE) using the finite element method.…
Optimal strong convergence rates of some Euler-type timestepping schemes for the finite element discretization SPDEs driven by additive fractional Brownian motion and Poisson random measure
Aurelien Junior Noupelah, Antoine Tambue
In this paper, we study the numerical approximation of a general second order semilinear stochastic partial differential equation (SPDE) driven by a additive fractional Brownian mo…
A fitted L-Multi-point Flux Approximation method for pricing options
Rock Stephane Koffi, Antoine Tambue
In this paper, we introduce a special kind of finite volume method called Multi-Point Flux Approximation method (MPFA) to price European and American options in two dimensional dom…
Convergence of the Two Point Flux Approximation and a novel fitted Two-Point Flux Approximation method for pricing options
Rock S. Koffi, Antoine Tambue
In this paper, we deal with numerical approximations for solving the Black-Scholes Partial Differential Equation (PDE). This PDE is well known to be degenerated. The space discreti…
Strong convergence of the backward Euler approximation for the finite element discretization of semilinear parabolic SPDEs with non-global Lipschitz drift driven by additive noise
Jean Daniel Mukam, Antoine Tambue
This paper deals with the backward Euler method applied to semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive noise. The SPDE is discretized…
A Fitted Multi-Point Flux Approximation Method for Pricing two options
Rock Stephane Koffi, Antoine Tambue
In this paper, we develop novel numerical methods based on the Multi-Point Flux Approximation (MPFA) method to solve the degenerated partial differential equation (PDE) arising fro…
Strong Convergence of the Linear Implicit Euler Method for the Finite Element Discretization of Semilinear non-Autonomous SPDEs Driven by Multiplicative or Additive Noise
Jean Daniel Mukam, Antoine Tambue
This paper aims to investigate the numerical approximation of semilinear non-autonomous stochastic partial differential equations (SPDEs) driven by multiplicative or additive noise…
Magnus-type integrator for the finite element discretization of semilinear parabolic non-autonomous SPDEs driven by additive noise
Jean Daniel Mukam, Antoine Tambue
In this paper, we investigate a numerical approximation of a general second order semilinear parabolic non-autonomous stochastic partial differential equation (SPDE) driven by addi…
Magnus-type Integrator for the Finite Element Discretization of Semilinear Parabolic non-Autonomous SPDEs Driven by multiplicative noise
Antoine Tambue, Jean Daniel Mukam
This paper aims to investigate numerical approximation of a general second order non-autonomous semilinear parabolic stochastic partial differential equation (SPDE) driven by multi…
Convergence analysis of the Magnus-Rosenbrock type method for the finite element discretization of semilinear non-autonomous parabolic PDEs with nonsmooth initial data
Antoine Tambue, Jean Daniel Mukam
This paper aims to investigate a full numerical approximation of non-autonomous semilnear parabolic partial differential equations (PDEs) with nonsmooth initial data. Our main inte…
Strong Convergence of a Stochastic Rosenbrock-type Scheme for the Finite Element Discretization of Semilinear SPDEs Driven by Multiplicative and Additive Noise
Jean Daniel Mukam, Antoine Tambue
This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive…
Strong Convergence of the Linear Implicit Euler Method for the Finite Element Discretization of Semilinear SPDEs Driven by Multiplicative and Additive Noise
Antoine Tambue, Jean Daniel Mukam
This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive…
Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure
Jean Daniel Mukam, Antoine Tambue
This paper deals with the numerical approximation of semilinear parabolic stochastic partial differential equation (SPDE) driven simultaneously by Gaussian noise and Poisson random…