Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

GitHub - SciML/OperatorLearning.jl: No need to train, he's a smooth operator

The DeepONets for Finance: An Approach to Calibrate the Heston Model

PDF) Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

Seminars — MPML.

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

PDF] Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks

The Universal Approximation Theorem – deep mind

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PDF) DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions

In-context operator learning with data prompts for differential equation problems

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

Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs