Pages that link to "Item:Q2117337"
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The following pages link to The Barron space and the flow-induced function spaces for neural network models (Q2117337):
Displaying 37 items.
- Understanding neural networks with reproducing kernel Banach spaces (Q2105111) (← links)
- Nonconvex regularization for sparse neural networks (Q2168678) (← links)
- Learning the mapping \(\mathbf{x}\mapsto \sum\limits_{i=1}^d x_i^2\): the cost of finding the needle in a haystack (Q2667355) (← links)
- Active learning based sampling for high-dimensional nonlinear partial differential equations (Q2683063) (← links)
- Low-rank kernel approximation of Lyapunov functions using neural networks (Q2696116) (← links)
- Greedy training algorithms for neural networks and applications to PDEs (Q2699382) (← links)
- Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning (Q5019943) (← links)
- Deep Adaptive Basis Galerkin Method for High-Dimensional Evolution Equations With Oscillatory Solutions (Q5038412) (← links)
- Two-Layer Neural Networks with Values in a Banach Space (Q5055293) (← links)
- Deep Ritz Method for the Spectral Fractional Laplacian Equation Using the Caffarelli--Silvestre Extension (Q5095480) (← links)
- The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation (Q5096451) (← links)
- Deep ReLU neural networks overcome the curse of dimensionality for partial integrodifferential equations (Q5873924) (← links)
- A New Function Space from Barron Class and Application to Neural Network Approximation (Q5878925) (← links)
- Simultaneous neural network approximation for smooth functions (Q6052416) (← links)
- Deep Neural Networks for Solving Large Linear Systems Arising from High-Dimensional Problems (Q6054285) (← links)
- Finite difference schemes for time-space fractional diffusion equations in one- and two-dimensions (Q6063576) (← links)
- Deep learning methods for partial differential equations and related parameter identification problems (Q6070739) (← links)
- A class of dimension-free metrics for the convergence of empirical measures (Q6072907) (← links)
- A priori generalization error analysis of two-layer neural networks for solving high dimensional Schrödinger eigenvalue problems (Q6076649) (← links)
- A finite difference scheme for the two-dimensional Gray-Scott equation with fractional Laplacian (Q6076935) (← links)
- A two-branch symmetric domain adaptation neural network based on Ulam stability theory (Q6127140) (← links)
- Improved Analysis of PINNs: Alleviate the CoD for Compositional Solutions (Q6151354) (← links)
- Learning High-Dimensional McKean–Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence (Q6184510) (← links)
- Control of neural transport for normalising flows (Q6187083) (← links)
- Two-layer networks with the \(\text{ReLU}^k\) activation function: Barron spaces and derivative approximation (Q6191372) (← links)
- Causal inference of general treatment effects using neural networks with a diverging number of confounders (Q6193012) (← links)
- A Reduced Order Schwarz Method for Nonlinear Multiscale Elliptic Equations Based on Two-Layer Neural Networks (Q6197994) (← links)
- A kernel framework for learning differential equations and their solution operators (Q6496499) (← links)
- Efficient and stable SAV-based methods for gradient flows arising from deep learning (Q6497260) (← links)
- Operator learning using random features: a tool for scientific computing (Q6585281) (← links)
- Generalization error in the deep Ritz method with smooth activation functions (Q6585908) (← links)
- Recovering the source term in elliptic equation via deep learning: method and convergence analysis (Q6586293) (← links)
- Numerical analysis of physics-informed neural networks and related models in physics-informed machine learning (Q6598418) (← links)
- Numerical solution of Poisson partial differential equation in high dimension using two-layer neural networks (Q6622387) (← links)
- Approximation results for gradient flow trained shallow neural networks in \(1d\) (Q6648717) (← links)
- Weighted variation spaces and approximation by shallow ReLU networks (Q6652573) (← links)
- Applied harmonic analysis and data science. Abstracts from the workshop held April 21--26, 2024 (Q6671618) (← links)
