Pages that link to "Item:Q2305540"
From MaRDI portal
The following pages link to Variational Monte Carlo -- bridging concepts of machine learning and high-dimensional partial differential equations (Q2305540):
Displaying 15 items.
- Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space (Q825596) (← links)
- Numerical solution of the parametric diffusion equation by deep neural networks (Q2049099) (← links)
- A theoretical analysis of deep neural networks and parametric PDEs (Q2117329) (← links)
- Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion (Q2128063) (← links)
- Variational problems in machine learning and their solution with finite elements (Q2796174) (← links)
- Convergence bounds for empirical nonlinear least-squares (Q5034774) (← links)
- (Q5149258) (← links)
- Approximative Policy Iteration for Exit Time Feedback Control Problems Driven by Stochastic Differential Equations using Tensor Train Format (Q5865245) (← links)
- Adaptive Nonintrusive Reconstruction of Solutions to High-Dimensional Parametric PDEs (Q6039259) (← links)
- Data-Driven Tensor Train Gradient Cross Approximation for Hamilton–Jacobi–Bellman Equations (Q6054276) (← links)
- Pricing High-Dimensional Bermudan Options with Hierarchical Tensor Formats (Q6159076) (← links)
- Randomized residual-based error estimators for the proper generalized decomposition approximation of parametrized problems (Q6554340) (← links)
- Mini-workshop: Nonlinear approximation of high-dimensional functions in scientific computing. Abstracts from the mini-workshop held October 15--20, 2023 (Q6613392) (← links)
- Approximating the stationary Bellman equation by hierarchical tensor products (Q6616995) (← links)
- Sample complexity bounds for the local convergence of least squares approximation (Q6649924) (← links)
