Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations

被引：0
|
作者：
Chen, Wenqian [1 ]
Stinis, Panos [1 ]
机构：
[1] Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, Richland,WA,99354, United States
来源：
arXiv | 2023年
关键词：
Compendex;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Machine learning
引用
收藏
相关论文
共 50 条
  • [1] Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations
    Chen, Wenqian
    Stinis, Panos
    JOURNAL OF COMPUTATIONAL PHYSICS, 2024, 498
  • [2] Multi-Fidelity Physics-Informed Generative Adversarial Network for Solving Partial Differential Equations
    Taghizadeh, Mehdi
    Nabian, Mohammad Amin
    Alemazkoor, Negin
    JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING, 2024, 24 (11)
  • [3] Multi-fidelity physics-informed machine learning for probabilistic damage diagnosis
    Miele, S.
    Karve, P.
    Mahadevan, S.
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 235
  • [4] A physics-informed impact model refined by multi-fidelity transfer learning
    Snapp, Kelsey L.
    Silverman, Samuel
    Pang, Richard
    Tiano, Thomas M.
    Lawton, Timothy J.
    Whiting, Emily
    Brown, Keith A.
    EXTREME MECHANICS LETTERS, 2024, 72
  • [5] Physics-informed machine learning for solving partial differential equations in porous media
    Shan, Liqun
    Liu, Chengqian
    Liu, Yanchang
    Tu, Yazhou
    Dong, Linyu
    Hei, Xiali
    ADVANCES IN GEO-ENERGY RESEARCH, 2023, 8 (01): : 37 - 44
  • [6] Multi-fidelity physics-informed machine learning framework for fatigue life prediction of additive manufactured materials
    Wang, Lanyi
    Zhu, Shun-Peng
    Wu, Borui
    Xu, Zijian
    Luo, Changqi
    Wang, Qingyuan
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2025, 439
  • [7] PHYSICS-INFORMED FOURIER NEURAL OPERATORS: A MACHINE LEARNING METHOD FOR PARAMETRIC PARTIAL DIFFERENTIAL EQUATIONS
    Zhang, Tao
    Xiao, Hui
    Ghosh, Debdulal
    JOURNAL OF NONLINEAR AND VARIATIONAL ANALYSIS, 2025, 9 (01): : 45 - 64
  • [8] Physics-informed multi-fidelity learning-driven imaging method for electrical capacitance tomography
    Lei, Jing
    Liu, Qibin
    Wang, Xueyao
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 116
  • [9] Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations
    Dalton, David
    Lazarus, Alan
    Gao, Gao
    Husmeier, Dirk
    JOURNAL OF MACHINE LEARNING RESEARCH, 2024, 25 : 1 - 61
  • [10] Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
    Wang, Sifan
    Wang, Hanwen
    Perdikaris, Paris
    SCIENCE ADVANCES, 2021, 7 (40)
12345