Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Por um escritor misterioso
Last updated 31 março 2025


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

Deep learning operator network for plastic deformation with variable loads and material properties

Algorithms, Free Full-Text

Operator Learning via Physics-Informed DeepONet: Let's Implement It From Scratch, by Shuai Guo

NEW PROGRESS IN INTELLIGENT SOLUTION OF NEURAL OPERATORS AND PHYSICS-INFORMED-BASED METHODS

A DeepONet multi-fidelity approach for residual learning in reduced order modeling, Advanced Modeling and Simulation in Engineering Sciences

VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification - ScienceDirect

Deep transfer operator learning for partial differential equations under conditional shift

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

DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators.
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