The following pages link to (Q4558489):
Displaying 47 items.
- Machine learning from a continuous viewpoint. I (Q829085) (← links)
- Deep neural networks motivated by partial differential equations (Q1988348) (← links)
- Variational networks: an optimal control approach to early stopping variational methods for image restoration (Q1988355) (← links)
- Selection dynamics for deep neural networks (Q2003969) (← links)
- Gradient convergence of deep learning-based numerical methods for BSDEs (Q2044106) (← links)
- A sequential quadratic Hamiltonian algorithm for training explicit RK neural networks (Q2068636) (← links)
- Estimating adsorption isotherm parameters in chromatography via a virtual injection promoting double feed-forward neural network (Q2082130) (← links)
- A measure theoretical approach to the mean-field maximum principle for training NeurODEs (Q2105521) (← links)
- Do ideas have shape? Idea registration as the continuous limit of artificial neural networks (Q2111734) (← links)
- On the regularized risk of distributionally robust learning over deep neural networks (Q2168882) (← links)
- Symplectic Runge-Kutta discretization of a regularized forward-backward sweep iteration for optimal control problems (Q2199787) (← links)
- A review on deep learning in medical image reconstruction (Q2218098) (← links)
- A modified MSA for stochastic control problems (Q2234329) (← links)
- Artificial neural network approximations of Cauchy inverse problem for linear PDEs (Q2247118) (← links)
- Deep learning as optimal control problems: models and numerical methods (Q2297872) (← links)
- A mean-field optimal control formulation of deep learning (Q2319864) (← links)
- Control on the manifolds of mappings with a view to the deep learning (Q2676673) (← links)
- Deep limits of residual neural networks (Q2679108) (← links)
- A Max-Sum algorithm for training discrete neural networks (Q3302364) (← links)
- Neural ODEs as the deep limit of ResNets with constant weights (Q4995042) (← links)
- (Q5011561) (← links)
- Structure-preserving deep learning (Q5014474) (← links)
- Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning (Q5019943) (← links)
- Maximal Function Pooling with Applications (Q5020148) (← links)
- (Q5054645) (← links)
- Personalized Algorithm Generation: A Case Study in Learning ODE Integrators (Q5088793) (← links)
- Machine Learning and Computational Mathematics (Q5162355) (← links)
- Explicit Stabilized Integrators for Stiff Optimal Control Problems (Q5857633) (← links)
- A Modified Method of Successive Approximations for Stochastic Recursive Optimal Control Problems (Q5869808) (← links)
- Turnpike in optimal control of PDEs, ResNets, and beyond (Q5887835) (← links)
- Principled deep neural network training through linear programming (Q6054389) (← links)
- Approximation capabilities of measure-preserving neural networks (Q6072433) (← links)
- Dual non-autonomous deep convolutional neural network for image denoising (Q6092092) (← links)
- Deep learning approximation of diffeomorphisms via linear-control systems (Q6099195) (← links)
- Sparsity in long-time control of neural ODEs (Q6099693) (← links)
- A mathematical perspective of machine learning (Q6118171) (← links)
- Linear Convergence of a Policy Gradient Method for Some Finite Horizon Continuous Time Control Problems (Q6140987) (← links)
- The Mori-Zwanzig formulation of deep learning (Q6162752) (← links)
- Deep learning via dynamical systems: an approximation perspective (Q6172665) (← links)
- An artificial neural network approach to identify the parameter in a nonlinear subdiffusion model (Q6177840) (← links)
- Optimal control using to approximate probability distribution of observation set (Q6189711) (← links)
- On mathematical modeling in image reconstruction and beyond (Q6200218) (← links)
- Efficient and stable SAV-based methods for gradient flows arising from deep learning (Q6497260) (← links)
- An optimal control framework for adaptive neural ODEs (Q6561374) (← links)
- An optimal control method to compute the most likely transition path for stochastic dynamical systems with jumps (Q6563609) (← links)
- Concurrent learning for adaptive Pontryagin's maximum principle of nonlinear systems with inequality constraints (Q6646987) (← links)
- Predict globally, correct locally: parallel-in-time optimization of neural networks (Q6659267) (← links)
