Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations-Reference-Cited by-同舟云学术

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Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations

Published:2024-11 Issue: Volume:431 Page:117265
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Kumar Sawan,Nayek Rajdip^ORCID,Chakraborty Souvik

Publisher

Elsevier BV

Reference48 articles.

1. Fourier neural operator for parametric partial differential equations;Li,2020

2. Deeponet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators;Lu,2019

3. Wavelet neural operator for solving parametric partial differential equations in computational mechanics problems;Tripura;Comput. Methods Appl. Mech. Engrg.,2023

4. FourCastNet: A global data-driven high-resolution weather model using adaptive Fourier neural operators;Pathak,2022

5. Spherical neural operator network for global weather prediction;Lin;IEEE Trans. Circuits Syst. Video Technol.,2023

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