An adaptive adjoint-oriented neural network for solving parametric optimal control problems with singularities
Fuente:
arXiv
Saved in:
| Main Authors: | Yuan, Zikang, Wang, Guanjie, Liao, Qifeng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Variational conditional normalizing flows for computing second-order mean field control problems
by: Zhao, Jiaxi, et al.
Published: (2025)
by: Zhao, Jiaxi, et al.
Published: (2025)
Convexity and strict convexity for compositional neural networks in high-dimensional optimal control
by: Grüne, Lars, et al.
Published: (2025)
by: Grüne, Lars, et al.
Published: (2025)
On the existence of minimizers in shallow residual ReLU neural network optimization landscapes
by: Dereich, Steffen, et al.
Published: (2023)
by: Dereich, Steffen, et al.
Published: (2023)
Separable Approximations of Optimal Value Functions and Their Representation by Neural Networks
by: Sperl, Mario, et al.
Published: (2025)
by: Sperl, Mario, et al.
Published: (2025)
An Operator Learning Approach to Nonsmooth Optimal Control of Nonlinear PDEs
by: Song, Yongcun, et al.
Published: (2024)
by: Song, Yongcun, et al.
Published: (2024)
On the existence of optimal shallow feedforward networks with ReLU activation
by: Dereich, Steffen, et al.
Published: (2023)
by: Dereich, Steffen, et al.
Published: (2023)
Constructive interpolation and generalization rates for neural ODEs: a control perspective
by: Álvarez-López, Antonio, et al.
Published: (2026)
by: Álvarez-López, Antonio, et al.
Published: (2026)
The Pontryagin Maximum Principle for Training Convolutional Neural Networks
by: Hofmann, Sebastian, et al.
Published: (2025)
by: Hofmann, Sebastian, et al.
Published: (2025)
Probability Density Estimation via Optimal Control
by: Hegland, Markus, et al.
Published: (2025)
by: Hegland, Markus, et al.
Published: (2025)
Adversarial Physics-Informed Machine Learning for Robust Optimal Safe Predefined-Time Stabilization: A Game-Theoretic Approach
by: Kokolakis, Nick-Marios T., et al.
Published: (2025)
by: Kokolakis, Nick-Marios T., et al.
Published: (2025)
Representation results and error estimates for differential games with applications using neural networks
by: Bokanowski, Olivier, et al.
Published: (2024)
by: Bokanowski, Olivier, et al.
Published: (2024)
Learning to Control: The iUzawa-Net for Nonsmooth Optimal Control of Linear PDEs
by: Song, Yongcun, et al.
Published: (2026)
by: Song, Yongcun, et al.
Published: (2026)
A First Step Towards Mesh-Free Probabilistic Shape Optimization
by: Schmidt, Stephan, et al.
Published: (2026)
by: Schmidt, Stephan, et al.
Published: (2026)
A Single-Loop Bilevel Deep Learning Method for Optimal Control of Obstacle Problems
by: Song, Yongcun, et al.
Published: (2026)
by: Song, Yongcun, et al.
Published: (2026)
Stability properties of Minimal Gated Unit neural networks
by: De Carli, Stefano, et al.
Published: (2026)
by: De Carli, Stefano, et al.
Published: (2026)
Quadratic convergence of an SQP method for some optimization problems with applications to control theory
by: Casas, Eduardo, et al.
Published: (2025)
by: Casas, Eduardo, et al.
Published: (2025)
Interplay between depth and width for interpolation in neural ODEs
by: Álvarez-López, Antonio, et al.
Published: (2024)
by: Álvarez-López, Antonio, et al.
Published: (2024)
Convergence of Riemannian Stochastic Gradient Descents: Varying Batch Sizes And Nonstandard Batch Forming
by: Wu, Hao
Published: (2026)
by: Wu, Hao
Published: (2026)
Learning where to learn: Training data distribution optimization for scientific machine learning
by: Guerra, Nicolas, et al.
Published: (2025)
by: Guerra, Nicolas, et al.
Published: (2025)
A network based approach for unbalanced optimal transport on surfaces
by: Pan, Jiangong, et al.
Published: (2024)
by: Pan, Jiangong, et al.
Published: (2024)
A data-driven Fourier-mixture neural-network method for density estimation
by: Dang, Duy-Minh, et al.
Published: (2026)
by: Dang, Duy-Minh, et al.
Published: (2026)
PurSAMERE: Reliable Adversarial Purification via Sharpness-Aware Minimization of Expected Reconstruction Error
by: Hoang, Vinh, et al.
Published: (2026)
by: Hoang, Vinh, et al.
Published: (2026)
Some notes concerning preconditioning of linear parabolic optimal control problems
by: Blank, Luise
Published: (2024)
by: Blank, Luise
Published: (2024)
Coefficient identification of the regularized p-Stokes equations
by: Schmidt, Niko
Published: (2024)
by: Schmidt, Niko
Published: (2024)
Finite-difference least square methods for solving Hamilton-Jacobi equations using neural networks
by: Esteve-Yagüe, Carlos, et al.
Published: (2024)
by: Esteve-Yagüe, Carlos, et al.
Published: (2024)
An inexact semismooth Newton-Krylov method for semilinear elliptic optimal control problem
by: Chen, Shiqi, et al.
Published: (2025)
by: Chen, Shiqi, et al.
Published: (2025)
An optimal boundary control problem related to the time dependent Navier-Stokes equations
by: Guerra, Telma, et al.
Published: (2024)
by: Guerra, Telma, et al.
Published: (2024)
Asymptotic compatibility of parametrized optimal design problems
by: Mengesha, Tadele, et al.
Published: (2024)
by: Mengesha, Tadele, et al.
Published: (2024)
Diagonal Linear Networks and the Lasso Regularization Path
by: Berthier, Raphaël
Published: (2025)
by: Berthier, Raphaël
Published: (2025)
The Hard-Constraint PINNs for Interface Optimal Control Problems
by: Lai, Ming-Chih, et al.
Published: (2023)
by: Lai, Ming-Chih, et al.
Published: (2023)
Conditional Density Estimation, Latent Variable Discovery and Optimal Transport
by: Yang, Hongkang, et al.
Published: (2019)
by: Yang, Hongkang, et al.
Published: (2019)
On the stabilization of a kinetic model by feedback-like control fields in a Monte Carlo framework
by: Bartsch, Jan, et al.
Published: (2023)
by: Bartsch, Jan, et al.
Published: (2023)
CLAIRE: Scalable GPU-Accelerated Algorithms for Diffeomorphic Image Registration in 3D
by: Mang, Andreas
Published: (2024)
by: Mang, Andreas
Published: (2024)
On the Identification and Optimization of Nonsmooth Superposition Operators in Semilinear Elliptic PDEs
by: Christof, Constantin, et al.
Published: (2023)
by: Christof, Constantin, et al.
Published: (2023)
Variational formulations of ODE-Net as a mean-field optimal control problem and existence results
by: Isobe, Noboru, et al.
Published: (2023)
by: Isobe, Noboru, et al.
Published: (2023)
Achieving Universal Approximation and Universal Interpolation via Nonlinearity of Control Families
by: Cai, Yongqiang, et al.
Published: (2025)
by: Cai, Yongqiang, et al.
Published: (2025)
Generic uniqueness and conjugate points for optimal control problems
by: Bressan, Alberto, et al.
Published: (2025)
by: Bressan, Alberto, et al.
Published: (2025)
Causality as the Statistical Conscience of Artificial Intelligence: From Pearl's Ladder to Trustworthy Machines
by: Fokoué, Ernest
Published: (2026)
by: Fokoué, Ernest
Published: (2026)
Stability analysis and optimal control of the logistic equation
by: Lemos-Silva, Márcia, et al.
Published: (2024)
by: Lemos-Silva, Márcia, et al.
Published: (2024)
Algebraic geometry of rational neural networks
by: Grosdos, Alexandros, et al.
Published: (2025)
by: Grosdos, Alexandros, et al.
Published: (2025)
Similar Items
-
Variational conditional normalizing flows for computing second-order mean field control problems
by: Zhao, Jiaxi, et al.
Published: (2025) -
Convexity and strict convexity for compositional neural networks in high-dimensional optimal control
by: Grüne, Lars, et al.
Published: (2025) -
On the existence of minimizers in shallow residual ReLU neural network optimization landscapes
by: Dereich, Steffen, et al.
Published: (2023) -
Separable Approximations of Optimal Value Functions and Their Representation by Neural Networks
by: Sperl, Mario, et al.
Published: (2025) -
An Operator Learning Approach to Nonsmooth Optimal Control of Nonlinear PDEs
by: Song, Yongcun, et al.
Published: (2024)