Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
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Descrição
Lecture Notes in Deep Learning: Known Operator Learning - Part 2 - Pattern Recognition Lab
In-context operator learning with data prompts for differential equation problems
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
arxiv-sanity
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators – arXiv Vanity
Operator Learning via Physics-Informed DeepONet: Let's Implement It From Scratch, by Shuai Guo
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators – arXiv Vanity
PDF) 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
The Universal Approximation Theorem – deep mind
PDF) Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks
Physics-Informed Neural Operators
Operator Learning via Physics-Informed DeepONet: Let's Implement It From Scratch, by Shuai Guo
A seamless multiscale operator neural network for inferring bubble dynamics, Journal of Fluid Mechanics
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