Stochastic physics-informed neural ordinary differential equations

被引:0
|
作者
O'Leary, Jared [1 ]
Paulson, Joel A. [2 ]
Mesbah, Ali [1 ]
机构
[1] Department of Chemical and Biomolecular Engineering, University of California, Berkeley,CA,94720, United States
[2] Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus,OH,43210, United States
来源
关键词
This work is in part supported by the National Science Foundation under Grant 2112754;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [32] Physics-informed generator-encoder adversarial networks with latent space matching for stochastic differential equations
    Gao, Ruisong
    Yang, Min
    Zhang, Jin
    [J]. JOURNAL OF COMPUTATIONAL SCIENCE, 2024, 79
  • [33] Stochastic Memristor Modeling Framework Based on Physics-Informed Neural Networks
    Kim, Kyeongmin
    Lee, Jonghwan
    [J]. Applied Sciences (Switzerland), 2024, 14 (20):
  • [34] APIK: Active Physics-Informed Kriging Model with Partial Differential Equations
    Chen, Jialei
    Chen, Zhehui
    Zhang, Chuck
    Wu, C. F. Jeff
    [J]. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2022, 10 (01): : 481 - 506
  • [35] Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks
    Berrone, S.
    Canuto, C.
    Pintore, M.
    Sukumar, N.
    [J]. HELIYON, 2023, 9 (08)
  • [36] A novel optimization-based physics-informed neural network scheme for solving fractional differential equations
    Sivalingam S M
    Pushpendra Kumar
    V. Govindaraj
    [J]. Engineering with Computers, 2024, 40 : 855 - 865
  • [37] Approximating Partial Differential Equations with Physics-Informed Legendre Multiwavelets CNN
    Wang, Yahong
    Wang, Wenmin
    Yu, Cheng
    Sun, Hongbo
    Zhang, Ruimin
    [J]. FRACTAL AND FRACTIONAL, 2024, 8 (02)
  • [38] ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
    Yan, Junjun
    Chen, Xinhai
    Wang, Zhichao
    Zhoui, Enqiang
    Liu, Jie
    [J]. 2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, 2023,
  • [39] HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations
    Huang, Yao
    Hao, Wenrui
    Lin, Guang
    [J]. COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2022, 121 : 62 - 73
  • [40] Physics-informed neural networks for the shallow-water equations on the sphere
    Bihlo, Alex
    Popovych, Roman O.
    [J]. JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 456