Pages that link to "Item:Q4409376"

The following pages link to Universal Approximation of Multiple Nonlinear Operators by Neural Networks (Q4409376):

Displaying 10 items.

• The universal approximation capabilities of double \(2\pi\)-periodic approximate identity neural networks (Q521720) (← links)
• Adjoint-operators and non-adiabatic learning algorithms in neural networks (Q804485) (← links)
• The universal approximation capabilities of cylindrical approximate identity neural networks (Q1639386) (← links)
• Pointwise and uniform approximation by multivariate neural network operators of the max-product type (Q2418225) (← links)
• The universal approximation theorem for complex-valued neural networks (Q2689134) (← links)
• Adaptive Classification of Temporal Signals in Fixed-Weight Recurrent Neural Networks: An Existence Proof (Q3527192) (← links)
• Toward Best Approximation of Nonlinear Systems: A Case of Models with Memory (Q5485908) (← links)
• Multifidelity deep operator networks for data-driven and physics-informed problems (Q6048427) (← links)
• A hybrid deep neural operator/finite element method for ice-sheet modeling (Q6054205) (← links)
• Convergence rate of DeepONets for learning operators arising from advection-diffusion equations (Q6361196) (← links)