NP-ODE: Neural process aided ordinary differential equations for uncertainty quantification of finite element analysis-Reference-Cited by-同舟云学术

NP-ODE: Neural process aided ordinary differential equations for uncertainty quantification of finite element analysis

Published:2021-04-02 Issue: Volume: Page:1-16
ISSN:2472-5854
Container-title:IISE Transactions
language:en
Short-container-title:IISE Transactions

Author:

Wang Yinan¹^ORCID,Wang Kaiwen²^ORCID,Cai Wenjun²^ORCID,Yue Xiaowei¹^ORCID

Affiliation:

1. Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

2. Materials Science and Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

Funder

US National Science Foundation

Division of Civil, Mechanical and Manufacturing Innovation

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/24725854.2021.1891485

Reference29 articles.

1. Stochastic Kriging for Simulation Metamodeling

2. Bahdanau, D., Cho, K.H. and Bengio, Y. (2015) Neural machine translation by jointly learning to align and translate, in Proceedings of the 3rd International Conference on Learning Representations (ICLR).

3. Nelder–Mead Optimization of Elastic Metamaterials via Machine-Learning-Aided Surrogate Modeling

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Error homogenization in physics-informed neural networks for modeling in manufacturing;Journal of Manufacturing Systems;2023-12

2. A Review on Tribocorrosion Behavior of Aluminum Alloys: From Fundamental Mechanisms to Alloy Design Strategies;Corrosion and Materials Degradation;2023-10-18

3. Applications and prospects of machine learning for aerosol jet printing: A review;IISE Transactions;2023-08-04

4. Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions;Technometrics;2023-05-30