Pages that link to "Item:Q3078556"
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The following pages link to Solving BSDE with Adaptive Control Variate (Q3078556):
Displaying 31 items.
- Adaptive importance sampling in least-squares Monte Carlo algorithms for backward stochastic differential equations (Q516010) (← links)
- \(\mathbf L_2\)-time regularity of BSDEs with irregular terminal functions (Q981015) (← links)
- An asymptotic expansion for forward-backward SDEs: a Malliavin calculus approach (Q1627727) (← links)
- Perturbative expansion technique for non-linear FBSDEs with interacting particle method (Q2013321) (← links)
- Control variate selection for Monte Carlo integration (Q2058787) (← links)
- Multilevel Picard iterations for solving smooth semilinear parabolic heat equations (Q2063953) (← links)
- A fully backward representation of semilinear PDEs applied to the control of thermostatic loads in power systems (Q2066980) (← links)
- Solving BSDEs based on novel multi-step schemes and multilevel Monte Carlo (Q2088763) (← links)
- Multistep schemes for solving backward stochastic differential equations on GPU (Q2138198) (← links)
- On the speed of convergence of Picard iterations of backward stochastic differential equations (Q2165738) (← links)
- Overcoming the curse of dimensionality in the approximative pricing of financial derivatives with default risks (Q2201474) (← links)
- Pricing and hedging in incomplete markets with model uncertainty (Q2286877) (← 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)
- Reducing variance in the numerical solution of BSDEs (Q2376608) (← links)
- A numerical algorithm for a class of BSDEs via the branching process (Q2434758) (← links)
- Simulation of BSDEs by Wiener chaos expansion (Q2454405) (← links)
- Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations (Q2694433) (← links)
- An overview on deep learning-based approximation methods for partial differential equations (Q2697278) (← links)
- Linear regression MDP scheme for discrete backward stochastic differential equations under general conditions (Q2792367) (← links)
- Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs (Q2833537) (← links)
- Least-Squares Monte Carlo for Backward SDEs (Q2917434) (← links)
- Deep Splitting Method for Parabolic PDEs (Q4958922) (← links)
- A polynomial scheme of asymptotic expansion for backward SDEs and option pricing (Q5001141) (← links)
- Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning (Q5019943) (← links)
- Monte Carlo integration with a growing number of control variates (Q5205948) (← links)
- A Fourier Cosine Method for an Efficient Computation of Solutions to BSDEs (Q5254475) (← links)
- Convergence of a Robust Deep FBSDE Method for Stochastic Control (Q5886857) (← links)
- Numerical methods for backward stochastic differential equations: a survey (Q6158181) (← links)
- Stability of backward stochastic differential equations: the general Lipschitz case (Q6165206) (← links)
- Deep learning algorithms for solving high-dimensional nonlinear backward stochastic differential equations (Q6201366) (← links)
