Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Descrição
Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs
PDF) Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks
Physics-Informed Neural Operators
PDF) Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators.
Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs
PDF) Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators – arXiv Vanity
arxiv-sanity
Deep transfer operator learning for partial differential equations under conditional shift
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