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

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Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
High‐Precision and Fast Prediction of Regional Wind Fields in Near Space Using Neural‐Network Approximation of Operators - Chen - 2023 - Geophysical Research Letters - Wiley Online Library
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
PDF) Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
PDF) DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Operator Learning via Physics-Informed DeepONet: Let's Implement It From Scratch, by Shuai Guo
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
PDF] Physics-Informed Deep Neural Operator Networks
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Physics-Informed Deep Neural Network for Backward-in-Time Prediction: Application to Rayleigh–Bénard Convection in: Artificial Intelligence for the Earth Systems Volume 2 Issue 1 (2023)
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Lecture Notes in Deep Learning: Known Operator Learning - Part 2 - Pattern Recognition Lab
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
In-context operator learning with data prompts for differential equation problems
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
PDF) Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification - ScienceDirect
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
DeepONet: A deep neural network-based model to approximate linear and nonlinear operators
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
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