Pages that link to "Item:Q2683168"

The following pages link to Space-time error estimates for deep neural network approximations for differential equations (Q2683168):

Displaying 8 items.

• Approximations with deep neural networks in Sobolev time-space (Q5075578) (← links)
• A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black–Scholes Partial Differential Equations (Q5889064) (← links)
• Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation (Q6107984) (← links)
• Lower bounds for artificial neural network approximations: a proof that shallow neural networks fail to overcome the curse of dimensionality (Q6155895) (← links)
• Deep Weak Approximation of SDEs: A Spatial Approximation Scheme for Solving Kolmogorov Equations (Q6173002) (← links)
• Space-time error estimates for deep neural network approximations for differential equations (Q6323500) (← links)
• Neural network expression rates and applications of the deep parametric PDE method in counterparty credit risk (Q6549602) (← links)
• Overcoming the curse of dimensionality in the numerical approximation of high-dimensional semilinear elliptic partial differential equations (Q6645961) (← links)