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  • Physics-Driven Learning of the Steady Navier-Stokes Equations Using Deep Convolutional Neural Networks

    Hao Ma, Yuxuan Zhang, Nils Thuerey, Xiangyu Hu, Oskar J. Haidn
    2022-09-29
    42769 3348 Pages:715-736
  • Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks

    Yingzhou Li, Xiuyuan Cheng, Jianfeng Lu
    2020-11-18
    63722 3467 Pages:1838-1885
  • Towards the Efficient Calculation of Quantity of Interest from Steady Euler Equations II: A CNNs-Based Automatic Implementation

    Jingfeng Wang, Guanghui Hu
    2026-01-03
    1687 47 Pages:884-918
  • A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

    N. V. Jagtap, M. K. Mudunuru, K. B. Nakshatrala
    2021-12-06
    49367 4042 Pages:188-223
  • Data-Driven, Physics-Based Feature Extraction from Fluid Flow Fields Using Convolutional Neural Networks

    Carlos Michelén Ströfer, Jin-Long Wu, Heng Xiao & Eric Paterson
    2018-11-09
    66627 6161 Pages:625-650 Open-access
  • Hamiltonian Reduction Using a Convolutional Auto-Encoder Coupled to a Hamiltonian Neural Network

    Raphaël Côte, Emmanuel Franck, Laurent Navoret, Guillaume Steimer, Vincent Vigon
    2025-09-02
    11762 870 Pages:315-352
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