Pages that link to "Item:Q3382802"
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The following pages link to The Random Feature Model for Input-Output Maps between Banach Spaces (Q3382802):
Displaying 28 items.
- Learning phase field mean curvature flows with neural networks (Q2083658) (← links)
- Do ideas have shape? Idea registration as the continuous limit of artificial neural networks (Q2111734) (← links)
- Iterated Kalman methodology for inverse problems (Q2671376) (← links)
- Learning high-dimensional parametric maps via reduced basis adaptive residual networks (Q2679335) (← links)
- Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures (Q2688074) (← links)
- Local approximation of operators (Q2689140) (← links)
- MIONet: Learning Multiple-Input Operators via Tensor Product (Q5048574) (← links)
- Two-Layer Neural Networks with Values in a Banach Space (Q5055293) (← links)
- Reduced Operator Inference for Nonlinear Partial Differential Equations (Q5088794) (← links)
- Variational regularization in inverse problems and machine learning (Q6064560) (← links)
- A framework for machine learning of model error in dynamical systems (Q6076655) (← links)
- Convergence Rates for Learning Linear Operators from Noisy Data (Q6109175) (← links)
- Transferable neural networks for partial differential equations (Q6123346) (← links)
- Sparse Recovery of Elliptic Solvers from Matrix-Vector Products (Q6154205) (← links)
- Large-scale Bayesian optimal experimental design with derivative-informed projected neural network (Q6159007) (← links)
- SPADE4: sparsity and delay embedding based forecasting of epidemics (Q6168035) (← links)
- Energy-dissipative evolutionary deep operator neural networks (Q6187616) (← links)
- Fast macroscopic forcing method (Q6196620) (← links)
- Optimal Dirichlet boundary control by Fourier neural operators applied to nonlinear optics (Q6196628) (← links)
- Derivative-informed neural operator: an efficient framework for high-dimensional parametric derivative learning (Q6202135) (← links)
- The Random Feature Model for Input-Output Maps between Banach Spaces (Q6341116) (← links)
- Multi-scale time-stepping of partial differential equations with transformers (Q6550140) (← links)
- Learning about structural errors in models of complex dynamical systems (Q6572173) (← links)
- Koopman neural operator as a mesh-free solver of non-linear partial differential equations (Q6572200) (← links)
- Learning homogenization for elliptic operators (Q6583661) (← links)
- Operator learning using random features: a tool for scientific computing (Q6585281) (← links)
- RandONets: shallow networks with random projections for learning linear and nonlinear operators (Q6648362) (← links)
- An enhanced V-cycle MgNet model for operator learning in numerical partial differential equations (Q6662449) (← links)
