Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Por um escritor misterioso
Descrição
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
A DeepONet multi-fidelity approach for residual learning in reduced order modeling, Advanced Modeling and Simulation in Engineering Sciences
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.
PDF) Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Algorithms, Free Full-Text
Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions
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
Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs
de
por adulto (o preço varia de acordo com o tamanho do grupo)