Martingale deep learning for very high dimensional quasi-linear partial differential equations and stochastic optimal controls
Fuente:
arXiv
Saved in:
| Main Authors: | Cai, Wei, Fang, Shuixin, Zhang, Wenzhong, Zhou, Tao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Deep random difference method for high-dimensional quasilinear parabolic partial differential equations
by: Cai, Wei, et al.
Published: (2025)
by: Cai, Wei, et al.
Published: (2025)
Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems
by: Dereich, Steffen, et al.
Published: (2025)
by: Dereich, Steffen, et al.
Published: (2025)
Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024)
by: Dereich, Steffen, et al.
Published: (2024)
Iterative solvers for partial differential equations with dissipative structure: Operator preconditioning and optimal control
by: Mehrmann, Volker, et al.
Published: (2025)
by: Mehrmann, Volker, et al.
Published: (2025)
Convergence analysis for an implementable scheme to solve the linear-quadratic stochastic optimal control problem with stochastic wave equation
by: Chaudhary, Abhishek
Published: (2025)
by: Chaudhary, Abhishek
Published: (2025)
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models
by: Tomasetto, Matteo, et al.
Published: (2024)
by: Tomasetto, Matteo, et al.
Published: (2024)
Two-scale neural networks for optimal control of linear convection-dominated equations
by: Liu, Sijing, et al.
Published: (2026)
by: Liu, Sijing, et al.
Published: (2026)
On the convergence of stochastic variance reduced gradient for linear inverse problems
by: Jin, Bangti, et al.
Published: (2025)
by: Jin, Bangti, et al.
Published: (2025)
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control
by: Oster, Mathias, et al.
Published: (2024)
by: Oster, Mathias, et al.
Published: (2024)
Modelling sand ripples in mine countermeasure simulations by means of stochastic optimal control
by: Blondeel, Philippe, et al.
Published: (2024)
by: Blondeel, Philippe, et al.
Published: (2024)
Ordinary differential equations for regularized variational problems involving semi-discrete optimal transport
by: Cances, Adrien, et al.
Published: (2026)
by: Cances, Adrien, et al.
Published: (2026)
Unidimensional semi-discrete partial optimal transport
by: Cances, Adrien, et al.
Published: (2025)
by: Cances, Adrien, et al.
Published: (2025)
Characterizing and computing solutions to regularized semi-discrete optimal transport via an ordinary differential equation
by: Nenna, Luca, et al.
Published: (2025)
by: Nenna, Luca, et al.
Published: (2025)
Error analysis for stochastic gradient optimization schemes using modified equations
by: Bréhier, Charles-Edouard, et al.
Published: (2024)
by: Bréhier, Charles-Edouard, et al.
Published: (2024)
SOC-MartNet: A Martingale Neural Network for the Hamilton-Jacobi-Bellman Equation without Explicit inf H in Stochastic Optimal Controls
by: Cai, Wei, et al.
Published: (2024)
by: Cai, Wei, et al.
Published: (2024)
Hierarchical clustering and dimensional reduction for optimal control of large-scale agent-based models
by: Monti, Angela, et al.
Published: (2025)
by: Monti, Angela, et al.
Published: (2025)
A novel shape optimization approach for source identification in elliptic equations
by: Gong, Wei, et al.
Published: (2024)
by: Gong, Wei, et al.
Published: (2024)
Convergence of the deep BSDE method for stochastic control problems formulated through the stochastic maximum principle
by: Huang, Zhipeng, et al.
Published: (2024)
by: Huang, Zhipeng, et al.
Published: (2024)
A finite element scheme for an optimal control problem on steady Navier-Stokes-Brinkman equations
by: Araneda, Jorge Aguayo, et al.
Published: (2025)
by: Araneda, Jorge Aguayo, et al.
Published: (2025)
Bilinear optimal control for the Stokes-Brinkman equations: a priori and a posteriori error analyses
by: Allendes, Alejandro, et al.
Published: (2024)
by: Allendes, Alejandro, et al.
Published: (2024)
Analysis of Robin-boundary control for the Boussinesq equations
by: Gong, Wei, et al.
Published: (2026)
by: Gong, Wei, et al.
Published: (2026)
Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
by: Jin, Qinian, et al.
Published: (2024)
by: Jin, Qinian, et al.
Published: (2024)
Numerical approximations for partially observed optimal control of stochastic partial differential equations
by: Bao, Feng, et al.
Published: (2025)
by: Bao, Feng, et al.
Published: (2025)
Convergence of differentiable non-monotone schemes for fully nonlinear parabolic equations
by: Nakano, Yumiharu
Published: (2018)
by: Nakano, Yumiharu
Published: (2018)
PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning
by: Jentzen, Arnulf, et al.
Published: (2025)
by: Jentzen, Arnulf, et al.
Published: (2025)
Reliable optimal controls for SEIR models in epidemiology
by: Cacace, Simone, et al.
Published: (2023)
by: Cacace, Simone, et al.
Published: (2023)
Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming
by: Cai, Yuhang, et al.
Published: (2025)
by: Cai, Yuhang, et al.
Published: (2025)
Convergence analysis of Lie and Strang splitting for operator-valued differential Riccati equations
by: Hansen, Eskil, et al.
Published: (2025)
by: Hansen, Eskil, et al.
Published: (2025)
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
by: Stollenwerk, Alexander, et al.
Published: (2024)
by: Stollenwerk, Alexander, et al.
Published: (2024)
Multilevel quadrature formulae for the optimal control of random PDEs
by: Nobile, Fabio, et al.
Published: (2024)
by: Nobile, Fabio, et al.
Published: (2024)
Bilinear optimal control for the fractional Laplacian: analysis and discretization
by: Bersetche, Francisco, et al.
Published: (2023)
by: Bersetche, Francisco, et al.
Published: (2023)
Stochastic dual coordinate descent with adaptive heavy ball momentum for linearly constrained convex optimization
by: Zeng, Yun, et al.
Published: (2023)
by: Zeng, Yun, et al.
Published: (2023)
Optimal control of a kinetic equation
by: Pim, Aaron, et al.
Published: (2024)
by: Pim, Aaron, et al.
Published: (2024)
The turnpike control in stochastic multi-agent dynamics: a discrete-time approach with exponential integrators
by: Cassini, Fabio, et al.
Published: (2025)
by: Cassini, Fabio, et al.
Published: (2025)
The turnpike property for high-dimensional interacting agent systems in discrete time
by: Gugat, Martin, et al.
Published: (2024)
by: Gugat, Martin, et al.
Published: (2024)
Deep Neural networks for solving high-dimensional parabolic partial differential equations
by: Zhang, Wenzhong, et al.
Published: (2026)
by: Zhang, Wenzhong, et al.
Published: (2026)
Efficient nonlocal linear image denoising: Bilevel optimization with Nonequispaced Fast Fourier Transform and matrix-free preconditioning
by: Miniguano-Trujillo, Andrés, et al.
Published: (2024)
by: Miniguano-Trujillo, Andrés, et al.
Published: (2024)
Primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric algebraic transformation
by: Kraria, Aicha, et al.
Published: (2024)
by: Kraria, Aicha, et al.
Published: (2024)
Non-overlapping Schwarz methods in time for parabolic optimal control problems
by: Gander, Martin Jakob, et al.
Published: (2024)
by: Gander, Martin Jakob, et al.
Published: (2024)
Numerical solution of elliptic distributed optimal control problems with boundary value tracking
by: Langer, Ulrich, et al.
Published: (2025)
by: Langer, Ulrich, et al.
Published: (2025)
Similar Items
-
Deep random difference method for high-dimensional quasilinear parabolic partial differential equations
by: Cai, Wei, et al.
Published: (2025) -
Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems
by: Dereich, Steffen, et al.
Published: (2025) -
Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024) -
Iterative solvers for partial differential equations with dissipative structure: Operator preconditioning and optimal control
by: Mehrmann, Volker, et al.
Published: (2025) -
Convergence analysis for an implementable scheme to solve the linear-quadratic stochastic optimal control problem with stochastic wave equation
by: Chaudhary, Abhishek
Published: (2025)