Multilevel Picard approximations of high-dimensional semilinear partial differential equations with locally monotone coefficient functions (Q2165859)

scientific article; zbMATH DE number 7574197

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English	Multilevel Picard approximations of high-dimensional semilinear partial differential equations with locally monotone coefficient functions	scientific article; zbMATH DE number 7574197

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instance of

scholarly article

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title

Multilevel Picard approximations of high-dimensional semilinear partial differential equations with locally monotone coefficient functions (English)

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Applied Numerical Mathematics

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publication date

23 August 2022

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full work available at URL

https://arxiv.org/abs/2202.02582

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zbMATH Keywords

curse of dimensionality

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high-dimensional PDEs

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multilevel Picard approximations

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multilevel Monte Carlo method

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locally monotone

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tamed Euler-type approximation

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MaRDI profile type

Publication

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cites work

Tensor networks and hierarchical tensors for the solution of high-dimensional partial differential equations

0 references

A quantization algorithm for solving multidimensional discrete-time optimal stopping problems

0 references

Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations

0 references

On existence and uniqueness properties for solutions of stochastic fixed point equations

0 references

Deep optimal stopping

0 references

On nonlinear Feynman–Kac formulas for viscosity solutions of semilinear parabolic partial differential equations

0 references

A forward scheme for backward SDEs

0 references

A PRIMAL–DUAL ALGORITHM FOR BSDES

0 references

Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations

0 references

Simulation of BSDEs by Wiener chaos expansion

0 references

Machine learning for semi linear PDEs

0 references

Convergence rates of best \(N\)-term Galerkin approximations for a class of elliptic SPDEs

0 references

Stochastic Equations in Infinite Dimensions

0 references

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

0 references

On multilevel Picard numerical approximations for high-dimensional nonlinear parabolic partial differential equations and high-dimensional nonlinear backward stochastic differential equations

0 references

Multilevel Picard iterations for solving smooth semilinear parabolic heat equations

0 references

The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems

0 references

Backward Stochastic Differential Equations in Finance

0 references

DNN expression rate analysis of high-dimensional PDEs: application to option pricing

0 references

A probabilistic numerical method for fully nonlinear parabolic PDEs

0 references

Asymptotic expansion as prior knowledge in deep learning method for high dimensional BSDEs

0 references

Multilevel Monte Carlo Path Simulation

0 references

A regression-based Monte Carlo method to solve backward stochastic differential equations

0 references

A monotone scheme for high-dimensional fully nonlinear PDEs

0 references

Existence of strong solutions for Itô's stochastic equations via approximations

0 references

Solving high-dimensional partial differential equations using deep learning

0 references

Branching diffusion representation of semilinear PDEs and Monte Carlo approximation

0 references

A numerical algorithm for a class of BSDEs via the branching process

0 references

Deep backward schemes for high-dimensional nonlinear PDEs

0 references

Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients

0 references

On a perturbation theory and on strong convergence rates for stochastic ordinary and partial differential equations with nonglobally monotone coefficients

0 references

Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients

0 references

Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients

0 references

Divergence of the multilevel Monte Carlo Euler method for nonlinear stochastic differential equations

0 references

Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations

0 references

Overcoming the curse of dimensionality in the approximative pricing of financial derivatives with default risks

0 references

Exponential integrability properties of numerical approximation processes for nonlinear stochastic differential equations

0 references

Exponential moments for numerical approximations of stochastic partial differential equations

0 references

DGM: a deep learning algorithm for solving partial differential equations

0 references

Branching Diffusion Processes

0 references

Q5600030

0 references

A Sparse-Grid Method for Multi-Dimensional Backward Stochastic Differential Equations

0 references

Identifiers

Mathematics Subject Classification ID

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10.1016/J.APNUM.2022.05.009

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Sitelinks

Mathematics(1 entry)

mardi Publication:2165859