Pages that link to "Item:Q783094"

The following pages link to Overcoming the curse of dimensionality for some Hamilton-Jacobi partial differential equations via neural network architectures (Q783094):

Displaying 40 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)
• Neural networks-based backward scheme for fully nonlinear PDEs (Q2022970) (← links)
• Computing Lyapunov functions using deep neural networks (Q2043422) (← links)
• Optimally weighted loss functions for solving PDEs with neural networks (Q2068635) (← links)
• A non-gradient method for solving elliptic partial differential equations with deep neural networks (Q2099748) (← links)
• On some neural network architectures that can represent viscosity solutions of certain high dimensional Hamilton-Jacobi partial differential equations (Q2123971) (← links)
• Solving inverse-PDE problems with physics-aware neural networks (Q2129334) (← links)
• An adaptive sparse grid local discontinuous Galerkin method for Hamilton-Jacobi equations in high dimensions (Q2131083) (← links)
• Newton's method, Bellman recursion and differential dynamic programming for unconstrained nonlinear dynamic games (Q2150657) (← links)
• RPINNs: rectified-physics informed neural networks for solving stationary partial differential equations (Q2166581) (← links)
• A physics-guided neural network framework for elastic plates: comparison of governing equations-based and energy-based approaches (Q2237330) (← links)
• Wasserstein generative adversarial uncertainty quantification in physics-informed neural networks (Q2671386) (← links)
• Physics and equality constrained artificial neural networks: application to forward and inverse problems with multi-fidelity data fusion (Q2671417) (← links)
• Neural network architectures using min-plus algebra for solving certain high-dimensional optimal control problems and Hamilton-Jacobi PDEs (Q2683498) (← links)
• State-dependent Riccati equation feedback stabilization for nonlinear PDEs (Q2692793) (← links)
• Mini-workshop: Analysis of data-driven optimal control. Abstracts from the mini-workshop held May 9--15, 2021 (hybrid meeting) (Q2693004) (← links)
• Physics-informed neural networks based on adaptive weighted loss functions for Hamilton-Jacobi equations (Q2694112) (← links)
• An overview on deep learning-based approximation methods for partial differential equations (Q2697278) (← links)
• Adaptive Deep Learning for High-Dimensional Hamilton--Jacobi--Bellman Equations (Q4997364) (← links)
• (Q4998939) (← links)
• Actor-Critic Method for High Dimensional Static Hamilton--Jacobi--Bellman Partial Differential Equations based on Neural Networks (Q5021407) (← links)
• An Algorithm to Construct Subsolutions of Convex Optimal Control Problems (Q5039275) (← links)
• SympOCnet: Solving Optimal Control Problems with Applications to High-Dimensional Multiagent Path Planning Problems (Q5058288) (← links)
• Feedforward Neural Networks and Compositional Functions with Applications to Dynamical Systems (Q5065061) (← links)
• Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats (Q5084512) (← links)
• On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs (Q5162370) (← links)
• Value-Gradient Based Formulation of Optimal Control Problem and Machine Learning Algorithm (Q6040292) (← links)
• Data-Driven Tensor Train Gradient Cross Approximation for Hamilton–Jacobi–Bellman Equations (Q6054276) (← links)
• Hamiltonian Deep Neural Networks Guaranteeing Nonvanishing Gradients by Design (Q6056086) (← links)
• Three ways to solve partial differential equations with neural networks — A review (Q6068232) (← links)
• Optimal polynomial feedback laws for finite horizon control problems (Q6072899) (← links)
• Sliding-mode surface-based approximate optimal control for nonlinear multiplayer Stackelberg-Nash games via adaptive dynamic programming (Q6118859) (← links)
• NeuralUQ: A Comprehensive Library for Uncertainty Quantification in Neural Differential Equations and Operators (Q6154538) (← links)
• Approximation of compositional functions with ReLU neural networks (Q6161370) (← links)
• Lax-Oleinik-type formulas and efficient algorithms for certain high-dimensional optimal control problems (Q6575313) (← links)
• Solving optimal control problems governed by nonlinear PDEs using a multilevel method based on an artificial neural network (Q6602281) (← links)
• Hamilton-Jacobi equations and mathematical morphology in pseudo-Riemannian manifolds (Q6610746) (← links)
• A tree structure approach to reachability analysis (Q6613474) (← links)
• A multilinear HJB-POD method for the optimal control of PDEs on a tree structure (Q6629218) (← links)
• Consistent smooth approximation of feedback laws for infinite horizon control problems with non-smooth value functions (Q6632963) (← links)