Pages that link to "Item:Q5021399"
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The following pages link to Approximation Error Analysis of Some Deep Backward Schemes for Nonlinear PDEs (Q5021399):
Displaying 13 items.
- Gradient boosting-based numerical methods for high-dimensional backward stochastic differential equations (Q2141183) (← links)
- DeepSets and their derivative networks for solving symmetric PDEs (Q2148121) (← links)
- Convergence of deep fictitious play for stochastic differential games (Q2170300) (← links)
- An overview on deep learning-based approximation methods for partial differential equations (Q2697278) (← links)
- A Neural Network Approach to High-Dimensional Optimal Switching Problems with Jumps in Energy Markets (Q6070671) (← links)
- Neural networks for first order HJB equations and application to front propagation with obstacle terms (Q6087416) (← links)
- Numerical methods for backward stochastic differential equations: a survey (Q6158181) (← links)
- Solving Kolmogorov PDEs without the curse of dimensionality via deep learning and asymptotic expansion with Malliavin calculus (Q6176082) (← links)
- Deep learning algorithms for solving high-dimensional nonlinear backward stochastic differential equations (Q6201366) (← links)
- A gradient method for high-dimensional BSDEs (Q6554575) (← links)
- A deep learning method for solving multi-dimensional coupled forward-backward doubly SDEs (Q6585377) (← links)
- High-dimensional stochastic control models for newsvendor problems and deep learning resolution (Q6589107) (← links)
- Numerical approximation of Dynkin games with asymmetric information (Q6663107) (← links)
