Pages that link to "Item:Q4933356"
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The following pages link to Probabilistic methods for semilinear partial differential equations. Applications to finance (Q4933356):
Displaying 14 items.
- Monte-Carlo algorithms for a forward Feynman-Kac-type representation for semilinear nonconservative partial differential equations (Q1746430) (← links)
- Sharp derivative bounds for solutions of degenerate semi-linear partial differential equations (Q1762334) (← links)
- Donsker-type theorem for BSDEs: rate of convergence (Q2040042) (← links)
- Overcoming the curse of dimensionality in the approximative pricing of financial derivatives with default risks (Q2201474) (← links)
- On multilevel Picard numerical approximations for high-dimensional nonlinear parabolic partial differential equations and high-dimensional nonlinear backward stochastic differential equations (Q2316188) (← links)
- Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations (Q2327815) (← links)
- Feynman-Kac representation of fully nonlinear PDEs and applications (Q2355853) (← links)
- Probabilistic approach to solution of nonlinear PDEs arising in financial mathematics (Q2452612) (← links)
- Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations (Q2694433) (← links)
- Deep Splitting Method for Parabolic PDEs (Q4958922) (← links)
- Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning (Q5019943) (← links)
- An Unbiased Itô Type Stochastic Representation for Transport PDEs: A Toy Example (Q5038297) (← links)
- Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations (Q5161194) (← links)
- Numerical methods for backward stochastic differential equations: a survey (Q6158181) (← links)
