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[1] Helmut Harbrecht, Michael Peters and Markus Siebenmorgen. On the quasi-Monte Carlo method with Halton points for elliptic PDEs with log-normal diffusion. Math. Comp.
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[2] Martin Sauer and Wilhelm Stannat. Analysis and approximation of stochastic nerve axon equations. Math. Comp. 85 (2016) 2457-2481.
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[3] Hoang-Long Ngo and Dai Taguchi. Strong rate of convergence for the Euler-Maruyama approximation of stochastic differential equations with irregular coefficients. Math. Comp. 85 (2016) 1793-1819.
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[4] Adam Andersson and Stig Larsson. Weak convergence for a spatial approximation of the nonlinear stochastic heat equation. Math. Comp. 85 (2016) 1335-1358.
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[5] Emmanuel Gobet and Plamen Turkedjiev. Linear regression MDP scheme for discrete backward stochastic differential equations under general conditions. Math. Comp. 85 (2016) 1359-1391.
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[6] Martin Sauer and Wilhelm Stannat. Lattice approximation for stochastic reaction diffusion equations with one-sided Lipschitz condition. Math. Comp. 84 (2015) 743-766.
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[7] Arturo Kohatsu-Higa, Salvador Ortiz-Latorre and Peter Tankov. Optimal simulation schemes for L\'evy driven stochastic differential equations. Math. Comp. 83 (2014) 2293-2324.
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[8] Tony Lelièvre, Mathias Rousset and Gabriel Stoltz. Langevin dynamics with constraints and computation of free energy differences. Math. Comp. 81 (2012) 2071-2125.
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[9] Carlos M. Mora. Numerical simulation of stochastic evolution equations associated to quantum Markov semigroups. Math. Comp. 73 (2004) 1393-1415. MR 2047093.
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[10] Arturo Kohatsu-Higa. Weak approximations. A Malliavin calculus approach. Math. Comp. 70 (2001) 135-172. MR 1680895.
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Results: 1 to 10 of 10 found      Go to page: 1


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